Design and Fabrication of Soft Prosthetic Hand

Design and Fabrication of Soft Prosthetic Hand | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Design and Fabrication of Soft Prosthetic Hand Tanveer Ahmed, Habibullah, Alishba Shah, Abdul Qayoom Soomro, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5812474/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study focuses on the development of soft robotic hand designed to aid individuals with hand disabilities, particularly those paralyzed due to strokes. Globally, strokes affect 15 million people annually, leading to 5 million deaths and leaving another 5 million with permanent disabilities that significantly impact their lives and communities. The soft robotic hand developed attempts to addresses the limitations of traditional robotic hands through the use of PneuNets, a pneumatic network framework that mimics the structure and function of a human hand. The hand's design incorporates pneumatic chambers that enable controlled finger movements, essential for grasping, lifting, and manipulating objects with precision. The primary components of the hand were fabricated using additive manufacturing and molding techniques, with a silicone outer layer added to enhance safety and compliance. The microcontroller-based control system is tailored to execute desired actions effectively, ensuring the soft hand’s adaptability to various tasks. Performance evaluations involved both simple and complex task profiles, demonstrating the hand's capability to handle a variety of objects with low variability in force and high precision. Specific technical results include the measurement of grasping forces, pressure requirements for actuation, and the assessment of attenuation losses during operation. Prior designs of soft robotic hands often suffer from issues like single-mode gripping and high attenuation losses; our approach mitigates these challenges through an optimized mechanical design coupled with learning algorithms that enhance grasping and manipulation efficiency. The soft characteristics of the robotic hand allow it to adapt its shape, making it capable of handling objects of varying sizes and shapes, thereby improving the daily functionality for individuals with hand impairments. This novel design not only offers increased independence and quality of life for patients but also provides a cost-effective and easily producible solution for wearable soft robotics. Robotics Soft Robotics PneuNets Stroke Rehabilitation Additive Manufacturing Wearable Robotic Hand Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 INTRODUCTION Every year, more than 795,000 people in the United States suffer from a stroke, with approximately 610,000 of these being first-time occurrences [1]. This causes major health issues such as hand paralysis, and hand impairments which make day to day chores simply a hazard to. To solve this, soft robotic hands and grippers are gaining prominent recognition as robotic end effector as they are safe to use, easy to control, flexible and low cost. Among them, soft fingers and actuator have grabbed quite an attention in the studies of soft robotic hand. The objective of our FYP was to develop a low-cost humanoid soft robotic hand with flexible sensing sensor. The need to improve the quality of life for people with hand impairments inspired us to research this topic. Current tools used for rehabilitation are not easy to use neither adaptable. So, we wanted to develop a wearable soft prosthetic hand to restore basic hand functioning which will allow the individual to perform daily chores with ease. Our project aims to incorporate advanced pneumatic actuation and tactile sensing technology in our hand. Stroke and Hand Paralysis Stroke is still a complex global health concern, which has a severe effect on the involved client. The CDC also mentions that in the United States more than 795000 stroke cases are recorded annually and can lead to such consequences as hand paralysis [5]. It underlines the need to have assistive technology and right methods of rehabilitation as it matters a lot. Soft Robotic Hands Soft robotic hands have become appealing as possible solutions because of their natural safety, flexibility, and safe interaction with environments. Unimproved soft robotic hand structure by using a soft palm like human palms were introduced by Wang et al [2], For the overall grasping actions. This design strategy underlines the importance of the imitation of such distinctive hand movements as are reflected in the nature to enhance such aspects as usability and functionality in daily use. Liu et al. The hybrid robotic grasping system was created by integrating deep multistage learning algorithms with soft multimodal grippers. According to their work, they have demonstrated how new learning algorithms make enhancements on the grip versatility, adaptability which is useful when handling numerous objects [3]. Extent of Integration of Sensing Technologies Thus, interface or tactile sensing technology is crucial in improving the performance and application of soft robotic hands. An artistically designed tendon-driven soft robotic gripper incorporating touch sensors was developed by Gunderman et al. , since such a gripper excels in operations such as blackberry harvesting [4]. In applications that need to be sensitive in handling, this integration assists in gain more control in gripping of objects and manipulation. Rehabilitation and Assistive applications Wearable sEMG sensors incorporated in soft robotic gloves have been shown to have the possibility of assisting hand paralysis individuals. For the assisted intuitive control and rehabilitation of the human hand for the individuals with compromised hand use, Cao and Zhang have developed a soft robotic glove with sEMG sensing integrated into it [4]. These devices use interactive feedback that assists in the rejuvenating of the motor functioning, and also provides a way of organizing the physical training. We see that a soft robotic glove developed for hand rehabilitation and task-oriented training by Polygerinos et al., was useful in the rehabilitation process. According specifically to their research, it is stressed that patients should be provided with wearable robotic devices to support task-oriented training programs contributing to enhancement of hand functioning and motor coordination in rehabilitation practice [5]. However, some challenges are still encountered in the aspect of soft robotics for hand rehabilitation though there have been lots of developments. Some of the problems that are being studied to date are the ones that relate to scalability, real-world performances, and integration of AI of higher levels for autonomous commanding [3][6][4]. In biomechanical applications as well as in industrial measurements and health care the pressure sensors are basic components because they are converting mechanical signals as force or pressure into an electrical signal [13]. Such sensors are utilized in biomechanical soft robots so that pressure distribution can be monitored secretly and continually across the fingers when handling objects [8] [10]. This integration enables patients to be assisted apply the right pressure while handling different objects and may also show level of pressure that is necessary and may be a sign of some clinical conditions like some diseases related to paralysis [11] [13]. A type of pressure sensors called piezoresistive pressure sensors work by altering their electrical resistance in response to pressure applied; this allows them to measure and detect changes in pressure [12]. For instance, graphene-based sponge pressure sensors, which provide the flexibility and comfort required for wearable devices, have been developed for applications such as rectal model pressure sensing [14] [15]. On the contrary, when incorporated into wearable devices, capacitive pressure sensors offer continuous, non-invasive pressure monitoring by measuring variations in capacitance [16]. The advances in CNT’s and Graphene have made pressure sensors more sensitive, flexible and much more durable than before [17] [18]. These materials have enabled the development of high sensitivity and flexibility in sensors and hence making them suitable to be used in wearable devices [19] [20]. One example of how pressure sensor technology is changing is flexible pressure sensor array with supercapacitor-piezo resistance system and with multi-channel wireless readout chip [21] [ 22]. For biomechanical studies, it is therefore very critical to choose the appropriate pressure sensor to quantify force and pressure at the joints during human movement appropriately. The application of pressure distribution map in real-time foundation is precisely suitable for the piezoresistive pressure sensors, which is recognized to have the ability to convert pressure mechanical variables into electrical ones in terms of changes in resistance ([20], [24]). The materials, including graphene, used in these sensors enhances their features especially sensitivity and flexibility that is required in the pressure differences in walking [14] [23]. Thus, capacitive pressure sensors which are based on changes of capacitance are very helpful for biomechanical investigations because they deliver real-time pressure distribution data during human movements [16] [25]. PDMS and MWCNTs incorporated into sensors cause the sensors to become more flexible and more sensitive, making them more appropriate in wearable technologies [26] [27]. Another method for measuring pressure distribution in biomechanical applications is the use of piezoelectric pressure sensors, which use the piezoelectric effect to generate an electric charge in response to mechanical stress [28] [29]. When embedded into the finger, these sensors allow continuous, non-invasive monitoring of pressure changes, providing valuable information about the biomechanics and mechanics of the finger [28] [29]. Comparison of some of the sensors we went through: Table. 2.1. Comparison of different papers BSFS [18] FOSS [9] Piezo-resistive [15] Stands for bimodal self-powered flexible sensor. Fiber Optics Shape Sensing. Piezoelectric + Resistive. Working Principle It is based on triboelectric nanogenerator and giant magnetoelastic effect. It works on the principle of OFDR. Change in electrical resistance is used to measure the pressure. Construction Magnetoelastic conductive film Packaged liquid metal coil Lumen co-molds. Teflon rods. FOSS. Cap. Degas in a vacuum chamber. Alloys of conductive materials. Characteristics It can precisely detect and distinguish touchless and tactile models. Response time of 10ms. The touchless signals give information about the object’s shape and material composition. Accuracy rate of up to 97%. It can detect bending and twisting along the entire length of the sensor. Enabling high fidelity full 3D state estimation. Sampling rates up to 250 Hz. Does not require knowledge of the mechanical properties. Simple construction and durability. a higher maximum operating temperature (up to about 200°C) well-suited to low-pressure applications, down to around 2 kPa. Advantages Describe complex objects. Precise manipulation tasks. Capacity to interpret and interact with the physical world. The fiber optic cable is compliant with a bending radius of curvature as low as 10 mm. It can accurately detect the shape and tip position of the soft actuator. Piezo-resistive strain gauge pressure sensors are robust. Their performance and calibration is also stable over time. Disadvantages The algorithms’ inability to describe unfamiliar objects. The system can only perform multimodal perception and description of objects it has been trained on. It cannot describe objects outside the training sets. It only gives us a finger size model for the actuator and is an open loop shape sensing system. They consume more power than some other types of pressure sensor. This may mean they are not suitable for battery powered or portable systems Feasibility of using it Didn’t need any self-powered sensor. Unavailability of inkjet printer. Its size is 10mm and the channel(tunnel) of the finger is only 2mm. Hence, we are unable to use this. They can be used in a soft robotic hand and are able to give robust result. They are also compatible with ecoflex material. Visual Representation of how we made the sensor: • Ecoflex part A was mixed with 0.16 gm of graphene nanocomposites. • The mixture was stirred with the help of a magnetic stirrer for 30 mins, which was then added with the Eco flex part B at a ratio of 1:1 to the Eco flex part A and stirred again for 30 mins. We had to work fast as Eco flex starts curing after 45 mins of mixing of part A and B. • The resulting GNPs/Eco flex nanocomposite solution was poured into a mold and cured under sunlight till it cures properly. • The rectangle film samples with the thickness of 2.5 mm were prepared for sensing test. • Both end sides of the GNPs/Eco flex nanocomposites were coated by copper (Cu) electrodes to reduce contact resistance before measurements. AI Integration in Soft Robotics To improve the usefulness and adaptability of robotic systems, artificial intelligence (AI) must be embedded in soft robotics. Soft robotic hands can function with far greater accuracy and responsiveness when controlled by AI-driven systems. For example, grip force and object manipulation can be optimized with learning-based control algorithms, enabling the robotic hand to dynamically adjust to different shapes and textures [3] [5]. The goal of this field's future research is to create increasingly complicated AI models that can function autonomously and make decisions in challenging situations [5] [3] [51]. SIMULATION For the analysis of the behavior of the soft actuator and hand, we viewed it through simulation. The design of the actuator was defined in SolidWorks first and then creating a STEP file which is required in the process of importing a solid works file in Ansys Software. Simulation of Single Figure First, we define the material for the actuator in ANSYS, selecting elastomer. Next, we import the STEP file prepared in SolidWorks. After this, we define the boundaries and create the mesh. We then select the locations where we will apply pressure and define gravity. We also specify the amount of pressure to be applied to actuate the finger. After setting these parameters, we move on to the solution phase, where we decide on the analyses to perform, such as total deformation, equivalent and elastic strain, and equivalent stress on a single finger. Finally, we run the simulation and obtain the results. We obtained a graph showing how deformation varies with pressure. Initially, a pressure of 15 kPa resulted in a deformation of 0.060 m. As the pressure increased, the deformation also increased, with a final pressure of 30 kPa causing a deformation of 0.082 m. This demonstrates that deformation increases with rising pressure. The graph highlights the initial pressure of 15 kPa and the final pressure of 30 kPa. Additionally, we obtain results for one finger or actuator of the hand, showing the relationship between time and deformation. Simulation of Complete Hand After performing the simulation for a single finger, we proceed to simulate the entire hand. We precisely position each finger in the hand's palm with accurate measurements. Following the same procedure as we did for a single finger, we define the material, import the STEP file, set boundaries, create the mesh, apply pressure, and define gravity. Upon running the simulation for the complete hand, we obtain the following results: To evaluate the design of the hand we checked its deformation behavior by applying pressure. First, we generated a graph showing the relationship between pressure and deformation for the entire hand, illustrating how the hand deforms under applied pressure. Second, we obtain a graph showing the relationship between time and deformation, indicating the extent of deformation over a specific period. This comprehensive approach provides valuable insights into the behavior of both individual fingers and the entire hand under various conditions, making it easier to design and create a practical soft robotic hand. METHODOLOGY As to the major objectives of our project we aimed at developing the prosthetic hand that should be lightweight, humanoid and comfortable to wear. The initial phase of the manufacturing process for this hand calls for a meticulous developmental process in SolidWorks with all dimensions and additional features inserted. That is followed by using this model as a mold to 3D print a different mold. Then another mold, which is a liquid silicone material, is then poured into the mold to dry and solidify to from the core of the hand. Finally, the prosthetic hand is built with the addition of a palm part designed for the specific user. Working on the Mold for the Actuator It is most preferable that it looks like a human hand and hence the design of the hand is made to look as natural as possible for acceptability. This paper adopted the SolidWorks software to design a mold of the first designs of the soft pneumatic actuators. Thus, the dimensions of the actuator were designated as L = 82 mm, W = 20 mm, CL = 12 mm, CW = 5 mm, and H = 10 mm if the human finger size is quite average. This chamber has an interior hole of 7 mm and a hall with a square of 2 mm to get an idea of the tube size. To achieve these requirements, the 3D model of the actuator was modeled carefully in SolidWorks environment with the help of regular modeling tools like extrusion, loft, sweep and fillet. Finally, a base mold was created that should fit the tunnel and upper portions of the actuator, in size of 86 mm in length and 26 mm in width. Working on the Mold for the Actuator The two critical processes in the making of the soft pneumatic actuators involved choosing the right material and proper casting. Thus, to obtain the desired flexibility, we chose Ecoflex 00-30 silicone rubber. To make one finger actuator, 15 grams of the silicone rubber (half of which is A and the other half is B) on a cup should be mixed thoroughly for at least three minutes. Finally, the achieved blend was tapped to get rid of presence of air bubbles which were crucial to achieving the best performance. Subsequently, the mixture of silicon was then gradually introduced into the prepared mold so as to minimizes the formation of new bubbles. The solution of the silicone was then left for the recommended four hours to harden after the filling of the mould. Once the curing cycle had been completed, the finished actuator was removed from the mold on most of the MMC system, and using a sharp knife or scissors No. 11, the excess rubber was finally trimmed to give the actuator a neat surface. Designing the Palm Several factors affect the usability and functionality of the soft pneumatic hand, including the palm. Concerning design, the gloves’ flexibility and comfort, as well as the way they fit various hand sizes and shapes were well mastered. In a bid of designing a hand that produces movements like those of a real palm, thus physical analysis on the palm of the human hand was conducted initially. To ensure they could receive the gloves and feel that they were truly comfortable, more variables such as the general length of fingers, space between the fingers, and range of motion of the fingers were considered. The first model created following the design was the cardboard model, which made it easier and cheaper to test on. The cardboard designed for minor changes and adjustments, provided the basic usability, comfort, and feasibility of the palm. Their shape, size, and all the considerable features might then be adjusted because there is an opportunity to use the CAD software to create the most accurate vision of what the hand will look like. The design was made even better particularly using expertise and user feedback. Last, 3D printing or molding procedures were applied to convert the final stage of the virtual model into tangible prototype. The actual palm was also tested through various experiments in this process to ensure that scores of performances ideal for a human like palm were achieved and tested in terms of gripping, grasping and overall ability to move things in a way in a human-like manner. Another method that involved relating feedback from users and the ergonomic assessments were made to effect changes. Integrating the Fingers with the Palm As the final step, incorporating the completed soft pneumatic fingers to the palm was done. For the fingers to fit properly the fingers were inserted properly into the palm mold which was developed uniquely. After that, Ecoflex-30 silicone was carefully poured into the mold, fulfilling two vital purposes: After that, Ecoflex-30 silicone was carefully poured into the mold, fulfilling two vital purposes: 1. Support Structure : The Eco flex provided a strong internal structure to hold the fingers in place within the palm, maintaining their proper alignment during movement. 2. Soft and Compliant Palm : The Eco flex created a soft and flexible palm, enhancing the hand's safety when interacting with objects and surfaces. The pouring process demanded precision to ensure complete filling of the mold. Once filled, the Eco flex cured and solidified, permanently integrating the fingers with the palm and completing the fabrication of the soft pneumatic hand. Control System A prosthetic hand must interact closely with the human body to be a useful artificial organ, and its control must be as instinctive and natural as possible. The soft pneumatic actuator in this study was precisely and accurately actuated by the pneumatic control system that was designed for it. It was made up of two pneumatic pumps that produced the required pressure for actuation: one for positive pressure and another for negative pressure. The solenoid valves that controlled the pumps' opening and closing were attached to these pumps. After that, the system-controlled airflow using a five-channel air distribution manifold, each of which was linked to a separate solenoid valve that controlled the amount of air that reached each finger. A general layout of the pneumatic system has been illustrated in the Fig.4.2. First module was made up of two solenoid-valves directly controlling the positive and negative pressures of the compressed air. These valves are all about the quick and accurate pressure management that delivers the best actuator performance possible. Five solenoid valves were included in the second module; one for finger movement and deformation of each one. As it would later be seen, each finger was connected to these actuators and this allowed independent control of each, thereby offering the ability to move and manipulate. A basic Arduino microcontroller motor driver was integrated into this pneumatic control system and it was a customized to give precise and timely strokes for the actuators with proper duration on the valves. The DC supply that was responsible for the microcontroller allowed the system to have all the power it required to operate. In this way the movements of the prosthetic hand were highly controlled and efficiently mimicked an actual human hand. 4.3 User Interface Application A user interface application was developed using the Visual Studio so as to make controlling of the soft pneumatic actuator easier. The given program provided a GUI interface possessed for controlling the actuator in real time. The software was very simple and more importantly, intuitive which allowed the users to dictate how the actuator should move. Concerning the mode of handling objects and performing various tasks such as rehabilitation besides gripping and handling objects like bottles as well as balls etc., options were supplied within the interface. The GUI has input boxes for setting the grip force for activities such as holding a bottle and the time for which it should release the bottle, along with the start/stop buttons. Users could input the degree of grip they wished to have before starting the action and the time of engagement before the structure released. This was helpful to the user because it meant that instead of the actuator determining the hand movement patterns and postures the user could program it to assume any desired hand positions. This way, the possibilities of the software being tested were discovered along with the fact that it allows the soft pneumatic actuator to be tested in various circumstances without any difficulty. It interfaced the application with the motor driver Arduino microcontroller through a serial communication port for real-time control of the pneumatic control system regarding the actuator movement. After considering all the parameters we realized that, the creation and testing of the soft pneumatic actuator relied heavily on the user interface application. It made it simple for users to experiment with various actuation patterns and combinations by enabling accurate and effective control. The straightforward design and extensive control options of the app enabled this full testing and evaluation of the actuator's capabilities. 4.4 Fabrication of Pressure Sensor Initially, 3D molds measuring 60 x 10 mm with a thickness of 1.25 mm were designed using SolidWorks 2016 and produced with an UltiMaker 3D printer and Cura software. A digital scale with a precision of 0.001g was employed to measure graphene Nano-powder, which had a thickness of 5-20 nm and an area size of 10 x 10 µm. The graphene weighed 16 mg. The graphene powder was thoroughly mixed with Ecoflex-0030, a silicone rubber provided in two parts (A and B) with a weight ratio of 1:1. This mixture was poured into the 3D-printed mold. The homogeneous Eco flex/Graphene blend could cure for 4 hours, resulting in a thin film of Eco-flex/Graphene composite. After curing, very thin layer of Ecoflex/Graphane was located between two copper (Cu) electrodes in order to produce high sensitive sensor base. It was then connected to the soft actuator of the hand as a sensor to read the data collected. These actuators were used to come up with a pneumatic hand for the disabled persons due to various physical impairments. The entire process is depicted in the following Fig. 4.5 RESULTS AND DISCUSSION The effectiveness of the developed soft robotic hand was demonstrated for several tasks that simulate gripping and holding tasks of the human hand. These activities included handling or picking up small and large objects, lifting weights and handling delicate items. The compliance and flexibility of the soft robotic hand proved to be useful for manipulation of objects of varying form and size since this simplifies the interaction of the tool with the surrounding environment for multiple purposes. Tasks performed by Hand Robot Grasping Task The grasping task was demonstrated by the soft robotic hand picking up objects of various dimensions including a bottle, a ball and some of the objects that are used in rehabilitation activities. The affectation of the hand provided the slippery objects to be gripped accurately and securely and the pneumatic actuated fingers of the hand were able to enclose the objects in their fingers and hold objects steady if the objects were tilted or rotated. The skin layer of the hand being soft and somewhat malleable in consistency ensured that the objects did not slide off and the user had a good grasp on the objects. Lifting Task The lifting task included the soft robotic hand lifting loads of various quantities and types for example a small load and a large load. Previously, the hand took the two types of weights and exerted significant force to lift them, proving its steadiness. With help of pneumatic actuation, the hand could regulate its force depending on the weight of the object and it would not slip or drop the object. Manipulation Task The manipulation task included using the soft robotic hand to pick up objects such as a piece of paper and foam ball. The outer layer of the hand is fleshy which disables it from becoming deformed by the nature of the object to be held as is the case with the mechanical hand. Thus, using the pneumatic actuation system the hand was sufficiently precise to place the necessary pressure on the object, without applying the damaging force. Evaluated on performance and analyzed statistically, the study demonstrated that the soft robotic hand was very reliable when it was used on different trials. The hand’s functionality and dexterity also meant that it was versatile in handling various sizes and shapes of the object, thus positively impacting the capabilities of the given individual to do many routine activities. Due to its lightweight and relatively cheap to produce, the soft robotic hand could be a viable solution for people in developing countries who are unable to gain access to highly technical prosthetic limbs. Characterization of Pneumatic System The functionalities of a prosthetic hand as a superior artificial limb depend on its interaction with the human body where such aspects as control system must be made natural. Regarding the control, a pneumatic control system was used in this work with objective of accurately controlling the soft pneumatic actuator to help improve the prosthetic hand advanced performance. To attain fine and stable control of the soft pneumatic actuator, the control system was interfaced with an Arduino micro controller. This microcontroller was used in regulating the time and period of validity of valves. The system could have a capacity of a pressure range of 400-650 mmHg which in Pascal is equivalent to 53. 23 to 86. 65. In addition, the negative pressure can be varied up to a maximum of the 46. 66 Pascal for the procedure. The applied pressure allowed the sizes of the pneumatic chambers to increase, which in its turn allowed the fingers to extend and open. GUI to Control our Pneumatic System TO control the soft pneumatic hand, the user interface application which was designed in Visual Studio and Tkinter was created. Python combined with GUI library called Tkinter is the best option to develop the graphical interface for Arduino solutions. Tkinter is the standard GUI library for Python supporting developing the efficient and simple interfaces. For the Game application, this use-case let users have a GUI of the actuator where they interact with the movements of the actuator in real-time. The app included nine possibilities of creating different pliages of the hand which allowed the user to control the actuator to obtain a desired hand form. Results of the experiments confirm that the soft pneumatic actuator is capable of fine grasping and manipulation in its tasks that require pick up small object and manipulate it. Doing these jobs, the actuator was able to perform with lots of precision and the result was constant which made it clear that it is so versatile that it can work in different tasks. Thus, the results of the study indicate that it is possible to develop, manufacture and control a soft pneumatic actuator to be incorporated into a robotic hand. Thanks to the precise control achievable by means of the control system and the user interface application and the flexibility and low weight of the actuator, this technology may be applied in various fields, namely robotics, manufacturing, and healthcare. All in all, the soft robotic hand that is featured in this thesis is accurate and precise as stated by the evaluation of gripping tests and the holding experiment results. Due its compliance and versatility, it offered generalized adaption to the shaped and sized objects in the conventional daily usage. Opening the dozens of videos of people with hand disabilities, softly moving fingers of the robotic hand can dramatically change the lives of those individuals and make them freer CONCLUSION AND FUTURE WORK Substantial advancements have been achieved in this thesis on the design, modeling and fabrication of soft robotic hands mainly in rehabilitation of individuals with paralysis because of strokes. This means that my thorough approach includes proper material selection of the arm contraption and its specific casting methods, so my current prosthetic hand is as light and mimics natural hand movements as much as the Hitec controlling mechanism allows. Significantly, the literature review touched on the possibilities of soft robotic hands due to their safety, elasticity, and ability for safe interaction with people. It also made a call for proper rehabilitation procedures and aids for the disabled persons as well as for technology to be enhanced. In an attempt to enhance the effectiveness of soft robotic hands, we reviewed several systems and enhancements such as incorporation of Tactile sensing and Hybrid grasping system. In the simulation chapter, we revisited how to do the actuator design in SolidWorks and prepare the STEP file from the design model for ANSYS software simulations. These simulations provided valuable information pertaining to the interaction and functionality of the hand as a single structure and each finger at different circumstances. The results lay the basis for the modification of the design and ensuring the functionality of the soft prosthetic hand. Some of the findings are general trends in deformation and relationship between pressure, time, and deformation. The fabrication process of the hand described in the methodology chapter was the way in which the mold of the actuator was made to the joining of the fingers and the palm, inclusive. Due to the extremity of Eco-flex 00-30 silicone rubber and optimized casting techniques, soft pneumatic actuators similar to human finger motion have been developed. In addition, due to developing the application to the graphical user interface the real-time control of actuators was enabled while, by testing all actuators at once, assessing their potential was significantly improved. All things considered, our work shows that soft robotics can be used to develop efficient rehabilitation tools that can greatly improve the quality of life for people with hand problems. The potential of soft robotic hands in both rehabilitative and assistive applications is demonstrated by the integration of cutting-edge materials, exact production techniques, and cutting-edge control systems. Future Work While this research has made substantial progress in the development of soft robotic hands, several areas warrant further exploration to enhance their functionality, scalability, and real-world applicability. Improvement of Material Properties:More attention should be paid to the development of new materials or further enhancement of the existing ones that would contribute to increasing the toughness and efficiency of soft pneumatic actuators. The more durable and flexible materials are needed for the prolonged usage or frequent usage in the rehabilitative settings; the more responsive material should also be investigated for further application. Integration of Advanced AI Introducing: more advanced AI models for improving the mechanization and automation of the soft robotic hands’ control systems would have great implications. Here several solutions are proposed: The ML algorithm could be used to fine-tune grip force and to predict patterns in the users’ movements, and to change as necessary depending on the task. This would allow the robotic hand to execute more detailed movements and change the exactness on how it is used first hand by the user. Scalability and Robustness: The problems associated with the increase in size and reliability in real-life conditions should be solved to advance the embrace of soft robotic hands. The further researches should be aimed at creating the mass production techniques, as well as on the devices’ ability to function in real-life conditions, including its interaction with various climatic conditions. Enhanced Sensing Technologies: Enhancement of the feedback mechanisms more advanced of tactile and pressure sensing technologies ascends the performance of soft robotic hands. Future innovation in sensors that yield better force distribution and object handling data in real time will improve the devices’ control and functions. User-Centric Design and Testing: This is because after the design process of soft robotic hands there is need for user feedback and ergonomic evaluations for the next design iteration. Trials with extensive users, that include people with different types and various degrees of hand impairment, will facilitate a better understanding of the real-life difficulties and preferable options. Personalized Rehabilitation Programs: It is possible to state that the application of soft robotics in creating individual patient’s rehabilitation plan could be the effective means to improve the progress of the recovery. Such programs could employ AI techniques in the data handling processes to choreograph individualized exercises and monitor the improvement, thus offering a better and more enjoyable approach to rehabilitation. In this way, future research would be established based on the findings of this thesis to reveal more efficient, reliable and user friendly soft robotic hands that could positively transform the lives of people with hand disabilities. Declarations ACKNOWLEDGEMENT This undergraduate level final year project was supported by Pakistan Engineering Council. References National Institute of Child Health and Human Development, "Stroke Risk Factors," National Institutes of Health, [Online]. Available: https://www.nichd.nih.gov/health/topics/stroke/conditioninfo/risk. [Accessed: Aug. 15, 2024]. H. Wang, F. J. Abu-Dakka, T. Le Nguyen, V. Kyrki, and H. Xu, “A Novel Soft Robotic Hand Design with Human-Inspired Soft Palm: Achieving a Great Diversity of Grasps,” IEEE Robot Autom Mag, vol. 28, no. 2, pp. 37–49, Jun. 2021, doi: 10.1109/MRA.2021.3065870. F. Liu, F. Sun, B. Fang, X. Li, S. Sun, and H. 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ABED, “Graphene preparation and graphite exfoliation,” 2021, TUBITAK. doi: 10.3906/kim-2101-19. D. Niu et al., “Graphene-elastomer nanocomposites based flexible piezoresistive sensors for strain and pressure detection,” Mater Res Bull, vol. 102, pp. 92–99, Jun. 2018, doi: 10.1016/j.materresbull.2018.02.005. M. Yang, Q. Liu, H. S. Naqawe, and M. P. Fok, “Movement Detection in Soft Robotic Gripper using Sinusoidally Embedded Fiber Optic Sensor,” Sensors, vol. 20, no. 5, p. 1312, Feb. 2020, doi: 10.3390/s20051312. K. C. Galloway, Y. Chen, E. Templeton, B. Rife, I. S. Godage, and E. J. Barth, “Fiber Optic Shape Sensing for Soft Robotics,” Soft Robotics, vol. 6, no. 5, pp. 671-684, Oct. 2019, doi: 10.1089/soro.2018.0131. W. Liu et al., “An Intelligent Robotic System Capable of Sensing and Describing Objects Based on Bimodal, Self-Powered Flexible Sensors,” Adv Funct Mater, vol. 33, no. 41, Oct. 2023, doi: 10.1002/adfm.202306368. H. Liu et al., “Electrically conductive thermoplastic elastomer nanocomposites at ultralow graphene loading levels for strain sensor applications,” J Mater Chem C Mater, vol. 4, no. 1, pp. 157–166, 2015, doi: 10.1039/c5tc02751a. L. Wang and L. Cheng, "Piezoresistive effect of a carbon nanotube silicone-matrix composite," Carbon, vol. 71, pp. 319-331, 2014, doi: 10.1016/j.carbon.2014.01.058 A. Ferreira and S. Lanceros-Mendez, "Piezoresistive response of spray-printed carbon nanotube/poly(vinylidene fluoride) composites," Composites Part B: Engineering, vol. 96, pp. 242-247, 2016, doi: 10.1016/j.compositesb.2016.03.098. M. A. Shmouty, M. H. M. Saadany, and A. R. Shmouty, "Hydraulic and Pneumatic Control in Mechatronics Systems (Article Review)," Processes, vol. 11, no. 3, 2023, doi: 10.3390/pr11030678. M. S. Xavier, A. J. Fleming, and Y. K. Yong, "Design and Control of Pneumatic Systems for Soft Robotics: A Simulation Approach," IEEE Robot. Autom. 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D. Marchese, R. K. Katzschmann, and D. Rus, "Modeling of Soft Robots Actuated by Twisted-and-Coiled Actuators," IEEE Trans. Robot., vol. 30, no. 3, pp. 550–558, Jun. 2014, doi: 10.1109/TRO.2014.2308553. P. Polygerinos, Z. Wang, K. C. Galloway, R. J. Wood, and C. J. Walsh, "Soft Robotics: A Review of Recent Developments of Pneumatic Soft Actuators," IEEE Robot. Autom. Mag., vol. 22, no. 3, pp. 28–44, Sep. 2015, doi: 10.1109/MRA.2015.2458201. C. G. Rose, F. Sergi, Y. Yun, K. Madden, A. D. Deshpande, and M. K. O’Malley, "Pneumatically Actuated Soft Robotic Hand and Wrist Exoskeleton for Motion Assistance in Rehabilitation," Actuators, vol. 13, no. 5, p. 180, May 2024, doi: 10.3390/act13050180. N. Mohammadi, J. Lavranos, H. Zhou, R. Mutlu, G. Alici, and Y. Tan, "A practical 3D-printed soft robotic prosthetic hand with multi-articulating capabilities," PLoS One, vol. 15, no. 5, p. e0232766, May 2020, doi: 10.1371/journal.pone.0232766. R. K. Tsiak, "Design Optimization of a Soft Robotic Rehabilitation Glove Based on Finger Workspace Analysis," Journal Name, vol. xx, no. yy, pp. zz-zz, Year. J. Polygerinos, Z. Wang, J. T. B. Overvelde, K. C. Galloway, R. J. Wood, and K. Bertoldi, "Modeling of soft fiber-reinforced bending actuators," IEEE Trans. Robot., vol. 31, no. 3, pp. 778–789, Jun. 2015, doi: 10.1109/TRO.2015.2428504. B. K. Bhargavi, J. F. Juslin, and A. R. Sharanya, "Design of Low-Cost Soft Robotic Hand," Propuls. Technol. J., vol. 44, no. 5, pp. 2805-2815, May 2023. C. G. Rose, F. Sergi, Y. Yun, K. Madden, A. D. Deshpande, and M. K. O'Malley, "Pneumatically Actuated Soft Robotic Hand and Wrist Exoskeleton for Motion Assistance in Rehabilitation," Actuators, vol. 13, no. 5, p. 180, May 2024, doi: 10.3390/act13050180. N. Mohammadi, J. Lavranos, H. Zhou, R. Mutlu, G. Alici, and Y. Tan, "A practical 3D-printed soft robotic prosthetic hand with multi-articulating capabilities," PLoS One, vol. 15, no. 5, p. e0232766, May 2020, doi: 10.1371/journal.pone.0232766. R. K. Tsiak, "Design Optimization of a Soft Robotic Rehabilitation Glove Based on Finger Workspace Analysis," Journal Name, vol. xx, no. yy, pp. zz-zz, J. Polygerinos, Z. Wang, J. T. B. Overvelde, K. C. Galloway, R. J. Wood, and K. Bertoldi, "Modeling of soft fiber-reinforced bending actuators," IEEE Trans. Robot., vol. 31, no. 3, pp. 778–789, Jun. 2015, doi: 10.1109/TRO.2015.2428504. B. K. Bhargavi, J. F. Juslin, and A. R. Sharanya, "Design of Low-Cost Soft Robotic Hand," Propuls. Technol. J., vol. 44, no. 5, pp. 2805-2815, May 2023. Z. Wang, Y. Torigoe, and S. Hirai, "A prestressed soft gripper: Design, modeling, fabrication, and tests for food handling," IEEE Robot. Autom. Lett., vol. 2, no. 4, pp. 1909-1916, Oct. 2017, doi: 10.1109/LRA.2017.2716445. Z. Niu, Y. Zhao, G. Gu, and X. Zhu, "Synergistic control of soft robotic hands for human-like grasp postures," Sci. China Technol. Sci., vol. 65, no. 1, pp. 1-13, Jan. 2022, doi: 10.1007/s11431-021-1944-y. A. N. Ghalati, H. Ghafarirad, A. A. Suratgar, M. Zareinejad, and M. A. Ahmadi-Pajouh, "Static modeling of soft reinforced bending actuator considering external force constraints," Soft Robot., vol. 9, no. 4, pp. 776-787, Aug. 2022, doi: 10.1089/soro.2021.0010. A. Mohammadi, J. Lavranos, H. Zhou, R. Mutlu, G. Alici, Y. Tan, et al., "A practical 3D-printed soft robotic prosthetic hand with multi-articulating capabilities," PLoS One, vol. 15, no. 5, p. e0232766, May 2020, doi: 10.1371/journal.pone.0232766. G. Alici, "Softer is harder: What differentiates soft robotics from hard robotics?," Adv. Intell. Syst., vol. 2, no. 12, p. 2000170, Dec. 2020, doi: 10.1002/aisy.202000170. C. D. Onal, X. Chen, M. T. Tolley, R. J. Wood, and D. Rus, "Soft mobile robots with on-board chemical pressure generation," J. Field Robot., vol. 32, no. 7, pp. 923-937, Oct. 2015, doi: 10.1002/rob.21567. F. Renda, J. Dias, C. Laschi, and M. Cianchetti, "Discrete Cosserat approach for soft robot dynamic modeling," IEEE Trans. Robot., vol. 34, no. 6, pp. 1518-1533, Dec. 2018, doi: 10.1109/TRO.2018.2868299. S. B. Kesner and R. D. Howe, "Design principles for rapid prototyping forces sensors using 3D printing," IEEE/ASME Trans. Mechatronics, vol. 22, no. 2, pp. 945-953, Apr. 2017, doi: 10.1109/TMECH.2017.2652766. K. C. Galloway, P. Polygerinos, C. J. Walsh, and R. J. Wood, "Mechanically programmable bend radius for fiber-reinforced soft actuators," Adv. Mater., vol. 25, no. 15, pp. 2361-2365, Apr. 2013, doi: 10.1002/adma.201204161. A. D. Marchese, C. D. Onal, and D. Rus, "Autonomous soft robotic fish capable of escape maneuvers using fluidic elastomer actuators," Soft Robot., vol. 1, no. 1, pp. 75-87, Mar. 2014, doi: 10.1089/soro.2013.0009. Robotics and Automation (ICRA), 2015 IEEE International Conference on : date, 26-30 May 2015. https://www.nichd.nih.gov/health/topics/stroke/conditioninfo/risk. [Accessed: Aug. 15, 2024]. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5812474","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":400987321,"identity":"2af6ac69-316e-4e8a-b7f9-084578218922","order_by":0,"name":"Tanveer Ahmed","email":"","orcid":"","institution":"Sukkur IBA University","correspondingAuthor":false,"prefix":"","firstName":"Tanveer","middleName":"","lastName":"Ahmed","suffix":""},{"id":400987322,"identity":"d6f19292-2036-4ba7-b2e1-c07a90878f22","order_by":1,"name":"Habibullah","email":"","orcid":"","institution":"Sukkur IBA University","correspondingAuthor":false,"prefix":"","firstName":"","middleName":"","lastName":"Habibullah","suffix":""},{"id":400987323,"identity":"bbe8e42e-c94a-46d6-92fc-6a55e1c7f8d9","order_by":2,"name":"Alishba Shah","email":"","orcid":"","institution":"Sukkur IBA University","correspondingAuthor":false,"prefix":"","firstName":"Alishba","middleName":"","lastName":"Shah","suffix":""},{"id":400988295,"identity":"acfe0493-8303-4b69-af8e-b9668c0c6a44","order_by":3,"name":"Abdul Qayoom Soomro","email":"","orcid":"","institution":"Sukkur IBA University","correspondingAuthor":false,"prefix":"","firstName":"Abdul","middleName":"Qayoom","lastName":"Soomro","suffix":""},{"id":400987324,"identity":"b93eeea2-b682-429e-8078-711a1769da1a","order_by":4,"name":"Afaque Manzoor Soomro","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYDAC5gPIvAqQCHMDfi1sCci8MyAtjKRoYWwDk/i18LcxP7zNU7FN3pz/8MHHlfNqo/nbgVp+VGzDqUXiGJuxNc+Z24Y7G44lG57ddjx3xmHGBsaeM7dxW3O/wUyat+0244aDPWaSjduO5TYAtTAztuHWIn+M/Zs077/b9hsO8wC1zDmWO5+QFoNjPEBbGm4nbjgG0tJQk7uBkBbDYzzFlnOO3U7ecIYt2bDh2IHcjUAtB/H5Re4Y+8Ybb2pu2244f/jgw4aautx5QMaDHxV4vA8EEkjsw2DyAF71aFrqCCkeBaNgFIyCEQgAri5efy57A1sAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-0352-9319","institution":"Sukkur IBA University","correspondingAuthor":true,"prefix":"","firstName":"Afaque","middleName":"Manzoor","lastName":"Soomro","suffix":""},{"id":400987325,"identity":"3a10afc3-ee1a-4042-bdf2-8e246265f56b","order_by":5,"name":"Umar Randhawa","email":"","orcid":"","institution":"Sukkur IBA University","correspondingAuthor":false,"prefix":"","firstName":"Umar","middleName":"","lastName":"Randhawa","suffix":""}],"badges":[],"createdAt":"2025-01-12 07:46:37","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5812474/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5812474/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73759463,"identity":"a96b0290-e835-4fcd-b0a4-e8525ac63fac","added_by":"auto","created_at":"2025-01-14 11:16:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":216724,"visible":true,"origin":"","legend":"\u003cp\u003eFig. 2.1. Sample preparation [15].\u003c/p\u003e","description":"","filename":"2.1.png","url":"https://assets-eu.researchsquare.com/files/rs-5812474/v1/85169748280bda59dfd52c72.png"},{"id":73759464,"identity":"190e6efa-2c57-43e5-a18a-acfe170274cd","added_by":"auto","created_at":"2025-01-14 11:16:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":73089,"visible":true,"origin":"","legend":"\u003cp\u003eFig. 3.1. Simulation of finger (Actuator) at different pressures and corresponding deformation: (a) We applied a pressure of 15 kpa, resulting in a deformation of 0.060 m. (b) We applied a pressure of 30 kpa, resulting in a deformation of 0.082 m. This indicates that deformation increases with increasing pressure.\u003c/p\u003e","description":"","filename":"3.1.png","url":"https://assets-eu.researchsquare.com/files/rs-5812474/v1/a888b6509bf9d83b85df231b.png"},{"id":73759476,"identity":"3c203edb-8544-4f20-b3d0-a483a4bc9015","added_by":"auto","created_at":"2025-01-14 11:16:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":75285,"visible":true,"origin":"","legend":"\u003cp\u003eFig. 3.2. The figure shows deformation at various pressures and their corresponding deformations: (a) Applying 15 kPa results in a deformation of approximately 0.060m. (b) Applying 20 kPa results in a deformation of approximately 0.068m.\u003cbr\u003e\n(c) Applying 25 kPa results in a deformation of approximately 0.075m.\u003cbr\u003e\n(d) Applying 30 kPa results in a deformation of approximately 0.082m.\u003c/p\u003e","description":"","filename":"3.2.png","url":"https://assets-eu.researchsquare.com/files/rs-5812474/v1/7beed5674d6b8ad22bd892a8.png"},{"id":73760687,"identity":"90c08c22-c872-4eac-a7da-773da954479a","added_by":"auto","created_at":"2025-01-14 11:24:41","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":58095,"visible":true,"origin":"","legend":"\u003cp\u003eFig. 3.3. Shows time versus deformation at various pressures: (a) Applying 15 kPa results in a deformation of 0.060 m in one second. (b) Applying 20 kPa results in a deformation of 0.068 m in one second. (c) Applying 25 kPa results in a deformation of 0.075 m in one second.(d) Applying 30 kPa results in a deformation of 0.082 m in one second. This indicates that as pressure increases, more deformation occurs within one second.\u003c/p\u003e","description":"","filename":"3.3.png","url":"https://assets-eu.researchsquare.com/files/rs-5812474/v1/b7f8be0265b5ade5a8568300.png"},{"id":73759472,"identity":"dca2a35d-ae59-439b-b610-44dadd75a09b","added_by":"auto","created_at":"2025-01-14 11:16:39","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":41443,"visible":true,"origin":"","legend":"\u003cp\u003eFig. 3.4. Shows the simulation of a complete soft robotic hand at various pressures and their corresponding deformations. The deformation increases as the pressure increases, with a pressure of 30 kPa resulting in a deformation of 0.125 m.\u003c/p\u003e","description":"","filename":"3.4.png","url":"https://assets-eu.researchsquare.com/files/rs-5812474/v1/141fdfbe7bfff8d6146c03d0.png"},{"id":73760703,"identity":"35d7d83b-f09a-4526-ac67-a434a5425a1e","added_by":"auto","created_at":"2025-01-14 11:24:44","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":27180,"visible":true,"origin":"","legend":"\u003cp\u003eFig. 3.5. Showing the relationship between pressure and deformation of a complete soft robotic hand: The deformation increases as the pressure increases, with 30 kPa resulting in a deformation of 0.125 m.\u003c/p\u003e","description":"","filename":"3.5.png","url":"https://assets-eu.researchsquare.com/files/rs-5812474/v1/420f73726694ccf90472ce1b.png"},{"id":73759465,"identity":"beebb28c-ab0b-43fb-82ac-02a7fd7707ad","added_by":"auto","created_at":"2025-01-14 11:16:39","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":25342,"visible":true,"origin":"","legend":"\u003cp\u003eFig. 3.6. Showing the relationship between time and deformation of a complete soft robotic hand: The deformation increases in one second as the pressure increases, with 30 kPa resulting in a deformation of 0.125 m in one second.\u003c/p\u003e","description":"","filename":"3.6.png","url":"https://assets-eu.researchsquare.com/files/rs-5812474/v1/bd536b8219a7bdf7c04aa500.png"},{"id":73759486,"identity":"d8358f89-32db-4c7c-967b-4e779ace15f3","added_by":"auto","created_at":"2025-01-14 11:16:40","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":272704,"visible":true,"origin":"","legend":"\u003cp\u003eFig. 4.1. Shows the design of the mold for an actuator: (a) Visual representation of the actuator. (b) Exterior part design in SolidWorks to hold the material. (c) Base mold designed to fit the tunnel and upper portions of the actuator. (d) Interior part of the actuator used to create air chambers.\u003c/p\u003e","description":"","filename":"4.1.png","url":"https://assets-eu.researchsquare.com/files/rs-5812474/v1/75570d6ac8ac20b74316a2df.png"},{"id":73760680,"identity":"849f674e-9823-4cdb-ae29-8dfdeefc0cd1","added_by":"auto","created_at":"2025-01-14 11:24:40","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":85009,"visible":true,"origin":"","legend":"\u003cp\u003eFig. 4.2. This figure illustrates the integration of fingers into the palm using SolidWorks. (a) The first finger is integrated, (b) followed by the second finger, (c) the third finger, (d) the fourth finger, and (e) the complete hand assembly is shown.\u003c/p\u003e","description":"","filename":"4.2.png","url":"https://assets-eu.researchsquare.com/files/rs-5812474/v1/01913287cc9b05a74d7037b6.png"},{"id":73759492,"identity":"bd50940c-a22b-45c2-a43b-a616395941f5","added_by":"auto","created_at":"2025-01-14 11:16:41","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":81111,"visible":true,"origin":"","legend":"\u003cp\u003eFig. 4.3. Pneumatic control system\u003c/p\u003e","description":"","filename":"4.3.png","url":"https://assets-eu.researchsquare.com/files/rs-5812474/v1/80a83a4338c1ea33a32b5d6b.png"},{"id":73759473,"identity":"cfcc3fe3-57b6-4421-a013-c73b7f67c02c","added_by":"auto","created_at":"2025-01-14 11:16:40","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":7156,"visible":true,"origin":"","legend":"\u003cp\u003eFig. 4.4. The figure shows the graphical user interface used to control the pressure applied to our soft robotic hand. It consists of five options: one for gripping a bottle, a second option for holding a ball, a third option for exercise, and start and stop button\u003c/p\u003e","description":"","filename":"4.4.png","url":"https://assets-eu.researchsquare.com/files/rs-5812474/v1/175cb1d1393905fe34c4b0f0.png"},{"id":73759494,"identity":"ddd644ed-0fc1-4972-a4d2-54958c851c90","added_by":"auto","created_at":"2025-01-14 11:16:41","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":145584,"visible":true,"origin":"","legend":"\u003cp\u003eFig. 4.5. Fabrication of Pressure Sensor\u003c/p\u003e","description":"","filename":"4.5.png","url":"https://assets-eu.researchsquare.com/files/rs-5812474/v1/c48b249c8edcd8ef79f9ef9e.png"},{"id":73761590,"identity":"04b8acb7-f967-43e7-acff-84ec549004bf","added_by":"auto","created_at":"2025-01-14 11:40:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1706615,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5812474/v1/30d9668e-5a1a-48e2-91a5-9addcfdcb19a.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eDesign and Fabrication of Soft Prosthetic Hand\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eEvery year, more than 795,000 people in the United States suffer from a stroke, with approximately 610,000 of these being first-time occurrences [1]. This causes major health issues such as hand paralysis, and hand impairments which make day to day chores simply a hazard to. To solve this, soft robotic hands and grippers are gaining prominent recognition as robotic end effector as they are safe to use, easy to control, flexible and low cost. Among them, soft fingers and actuator have grabbed quite an attention in the studies of soft robotic hand. The objective of our FYP was to develop a low-cost humanoid soft robotic hand with flexible sensing sensor. The need to improve the quality of life for people with hand impairments inspired us to research this topic. Current tools used for rehabilitation are not easy to use neither adaptable. So, we wanted to develop a wearable soft prosthetic hand to restore basic hand functioning which will allow the individual to perform daily chores with ease. Our project aims to incorporate advanced pneumatic actuation and tactile sensing technology in our hand. \u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eStroke and Hand Paralysis\u003c/h2\u003e\n\u003cp\u003eStroke is still a complex global health concern, which has a severe effect on the involved client. The CDC also mentions that in the United States more than 795000 stroke cases are recorded annually and can lead to such consequences as hand paralysis [5]. It underlines the need to have assistive technology and right methods of rehabilitation as it matters a lot.\u003c/p\u003e\n\u003ch2\u003e\u0026nbsp;Soft Robotic Hands \u0026nbsp;\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003e\u0026nbsp;Soft robotic hands have become appealing as possible solutions because of their natural safety, flexibility, and safe interaction with environments. Unimproved soft robotic hand structure by using a soft palm like human palms were introduced by Wang et al [2], For the overall grasping actions. This design strategy underlines the importance of the imitation of such distinctive hand movements as are reflected in the nature to enhance such aspects as usability and functionality in daily use.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Liu et al. The hybrid robotic grasping system was created by integrating deep multistage learning algorithms with soft multimodal grippers. According to their work, they have demonstrated how new learning algorithms make enhancements on the grip versatility, adaptability which is useful when handling numerous objects [3].\u003c/p\u003e\n\u003ch2\u003eExtent of Integration of Sensing Technologies\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003e\u0026nbsp;Thus, interface or tactile sensing technology is crucial in improving the performance and application of soft robotic hands. An artistically designed tendon-driven soft robotic gripper incorporating touch sensors was developed by Gunderman et al. , since such a gripper excels in operations such as blackberry harvesting [4]. In applications that need to be sensitive in handling, this integration assists in gain more control in gripping of objects and manipulation.\u003c/p\u003e\n\u003ch2\u003eRehabilitation and Assistive applications\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eWearable sEMG sensors incorporated in soft robotic gloves have been shown to have the possibility of assisting hand paralysis individuals. For the assisted intuitive control and rehabilitation of the human hand for the individuals with compromised hand use, Cao and Zhang have developed a soft robotic glove with sEMG sensing integrated into it [4]. These devices use interactive feedback that assists in the rejuvenating of the motor functioning, and also provides a way of organizing the physical training.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;We see that a soft robotic glove developed for hand rehabilitation and task-oriented training by Polygerinos et al., was useful in the rehabilitation process. According specifically to their research, it is stressed that patients should be provided with wearable robotic devices to support task-oriented training programs contributing to enhancement of hand functioning and motor coordination in rehabilitation practice [5]. However, some challenges are still encountered in the aspect of soft robotics for hand rehabilitation though there have been lots of developments. Some of the problems that are being studied to date are the ones that relate to scalability, real-world performances, and integration of AI of higher levels for autonomous commanding [3][6][4]. In biomechanical applications as well as in industrial measurements and health care the pressure sensors are basic components because they are converting mechanical signals as force or pressure into an electrical signal [13]. Such sensors are utilized in biomechanical soft robots so that pressure distribution can be monitored secretly and continually across the fingers when handling objects [8] [10]. This integration enables patients to be assisted apply the right pressure while handling different objects and may also show level of pressure that is necessary and may be a sign of some clinical conditions like some diseases related to paralysis [11] [13].\u003c/p\u003e\n\u003cp\u003eA type of pressure sensors called piezoresistive pressure sensors work by altering their electrical resistance in response to pressure applied; this allows them to measure and detect changes in pressure [12]. For instance, graphene-based sponge pressure sensors, which provide the flexibility and comfort required for wearable devices, have been developed for applications such as rectal model pressure sensing [14] [15]. On the contrary, when incorporated into wearable devices, capacitive pressure sensors offer continuous, non-invasive pressure monitoring by measuring variations in capacitance [16]. The advances in CNT\u0026rsquo;s and Graphene have made pressure sensors more sensitive, flexible and much more durable than before [17] [18]. These materials have enabled the development of high sensitivity and flexibility in sensors and hence making them suitable to be used in wearable devices [19] [20]. One example of how pressure sensor technology is changing is flexible pressure sensor array with supercapacitor-piezo resistance system and with multi-channel wireless readout chip [21] [ 22].\u003c/p\u003e\n\u003cp\u003eFor biomechanical studies, it is therefore very critical to choose the appropriate pressure sensor to quantify force and pressure at the joints during human movement appropriately. The application of pressure distribution map in real-time foundation is precisely suitable for the piezoresistive pressure sensors, which is recognized to have the ability to convert pressure mechanical variables into electrical ones in terms of changes in resistance ([20], [24]). The materials, including graphene, used in these sensors enhances their features especially sensitivity and flexibility that is required in the pressure differences in walking [14] [23].\u003c/p\u003e\n\u003cp\u003eThus, capacitive pressure sensors which are based on changes of capacitance are very helpful for biomechanical investigations because they deliver real-time pressure distribution data during human movements [16] [25]. PDMS and MWCNTs incorporated into sensors cause the sensors to become more flexible and more sensitive, making them more appropriate in wearable technologies [26] [27]. Another method for measuring pressure distribution in biomechanical applications is the use of piezoelectric pressure sensors, which use the piezoelectric effect to generate an electric charge in response to mechanical stress [28] [29]. When embedded into the finger, these sensors allow continuous, non-invasive monitoring of pressure changes, providing valuable information about the biomechanics and mechanics of the finger [28] [29]. Comparison of some of the sensors we went through:\u003c/p\u003e\n\u003cp\u003eTable. 2.1. Comparison of different papers\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBSFS [18]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFOSS [9]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePiezo-resistive [15]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eStands for\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003ebimodal self-powered flexible sensor.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eFiber Optics Shape Sensing.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 173px;\"\u003e\n \u003cp\u003ePiezoelectric + Resistive.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eWorking Principle\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eIt is based on triboelectric nanogenerator and giant magnetoelastic effect.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eIt works on the principle of OFDR.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 173px;\"\u003e\n \u003cp\u003eChange in electrical resistance is used to measure the pressure.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eConstruction\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eMagnetoelastic conductive film\u003c/p\u003e\n \u003cp\u003ePackaged liquid metal coil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eLumen co-molds. Teflon rods. FOSS. Cap. Degas in a vacuum chamber.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 173px;\"\u003e\n \u003cp\u003eAlloys of conductive materials.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eCharacteristics\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eIt can precisely detect and distinguish touchless and tactile models.\u003c/p\u003e\n \u003cp\u003eResponse time of 10ms.\u003c/p\u003e\n \u003cp\u003eThe touchless signals give information about the object\u0026rsquo;s shape and material composition.\u003c/p\u003e\n \u003cp\u003eAccuracy rate of up to 97%.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eIt can detect bending and twisting along the entire length of the sensor.\u003c/p\u003e\n \u003cp\u003eEnabling high fidelity full 3D state estimation.\u003c/p\u003e\n \u003cp\u003eSampling rates up to 250 Hz.\u003c/p\u003e\n \u003cp\u003eDoes not require knowledge of the mechanical properties.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 173px;\"\u003e\n \u003cp\u003eSimple construction and durability.\u003c/p\u003e\n \u003cp\u003ea higher maximum operating temperature (up to about 200\u0026deg;C)\u003c/p\u003e\n \u003cp\u003ewell-suited to low-pressure applications, down to around 2 kPa.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eAdvantages\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eDescribe complex objects.\u003c/p\u003e\n \u003cp\u003ePrecise manipulation tasks.\u003c/p\u003e\n \u003cp\u003eCapacity to interpret and interact with the physical world.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eThe fiber optic cable is compliant with a bending radius of curvature as low as 10 mm.\u003c/p\u003e\n \u003cp\u003eIt can accurately detect the shape and tip position of the soft actuator.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 173px;\"\u003e\n \u003cp\u003ePiezo-resistive strain gauge pressure sensors are robust. Their performance and calibration is also stable over time.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eDisadvantages\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eThe algorithms\u0026rsquo; inability to describe unfamiliar objects. The system can only perform multimodal perception and description of objects it has been trained on. It cannot describe objects outside the training sets.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eIt only gives us a finger size model for the actuator and is an open loop shape sensing system.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 173px;\"\u003e\n \u003cp\u003eThey consume more power than some other types of pressure sensor. This may mean they are not suitable for battery powered or portable systems\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eFeasibility of using it\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eDidn\u0026rsquo;t need any self-powered sensor.\u003c/p\u003e\n \u003cp\u003eUnavailability of inkjet printer.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eIts size is 10mm and the channel(tunnel) of the finger is only 2mm. Hence, we are unable to use this.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 173px;\"\u003e\n \u003cp\u003eThey can be used in a soft robotic hand and are able to give robust result.\u003c/p\u003e\n \u003cp\u003eThey are also compatible with ecoflex material.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eVisual Representation of how we made the sensor:\u003c/p\u003e\n\u003cp\u003e\u0026bull;\u0026nbsp; \u0026nbsp; \u0026nbsp;Ecoflex part A was mixed with 0.16 gm of graphene nanocomposites.\u003c/p\u003e\n\u003cp\u003e\u0026bull;\u0026nbsp; \u0026nbsp; \u0026nbsp;The mixture was stirred with the help of a magnetic stirrer for 30 mins, which was then added with the Eco flex part B at a ratio of 1:1 to the Eco flex part A and stirred again for 30 mins. We had to work fast as Eco flex starts curing after 45 mins of mixing of part A and B.\u003c/p\u003e\n\u003cp\u003e\u0026bull;\u0026nbsp; \u0026nbsp; \u0026nbsp;The resulting GNPs/Eco flex nanocomposite solution was poured into a mold and cured under sunlight till it cures properly.\u003c/p\u003e\n\u003cp\u003e\u0026bull;\u0026nbsp; \u0026nbsp; \u0026nbsp;The rectangle film samples with the thickness of 2.5 mm were prepared for sensing test.\u003c/p\u003e\n\u003cp\u003e\u0026bull;\u0026nbsp; \u0026nbsp; \u0026nbsp; Both end sides of the GNPs/Eco flex nanocomposites were coated by copper (Cu) electrodes to reduce contact resistance before measurements.\u003c/p\u003e\n\u003ch2\u003eAI Integration in Soft Robotics\u003c/h2\u003e\n\u003cp\u003eTo improve the usefulness and adaptability of robotic systems, artificial intelligence (AI) must be embedded in soft robotics. Soft robotic hands can function with far greater accuracy and responsiveness when controlled by AI-driven systems. For example, grip force and object manipulation can be optimized with learning-based control algorithms, enabling the robotic hand to dynamically adjust to different shapes and textures [3] [5]. The goal of this field\u0026apos;s future research is to create increasingly complicated AI models that can function autonomously and make decisions in challenging situations [5] [3] [51].\u003c/p\u003e"},{"header":"SIMULATION","content":"\u003cp\u003eFor the analysis of the behavior of the soft actuator and hand, we viewed it through simulation. The design of the actuator was defined in SolidWorks first and then creating a STEP file which is required in the process of importing a solid works file in Ansys Software.\u003c/p\u003e\n\u003ch2\u003eSimulation of Single Figure\u003c/h2\u003e\n\u003cp\u003eFirst, we define the material for the actuator in ANSYS, selecting elastomer. Next, we import the STEP file prepared in SolidWorks. After this, we define the boundaries and create the mesh. We then select the locations where we will apply pressure and define gravity. We also specify the amount of pressure to be applied to actuate the finger. After setting these parameters, we move on to the solution phase, where we decide on the analyses to perform, such as total deformation, equivalent and elastic strain, and equivalent stress on a single finger. Finally, we run the simulation and obtain the results.\u003c/p\u003e\n\u003cp\u003eWe obtained a graph showing how deformation varies with pressure. Initially, a pressure of 15 kPa resulted in a deformation of 0.060 m. As the pressure increased, the deformation also increased, with a final pressure of 30 kPa causing a deformation of 0.082 m. This demonstrates that deformation increases with rising pressure. The graph highlights the initial pressure of 15 kPa and the final pressure of 30 kPa.\u003c/p\u003e\n\u003cp\u003eAdditionally, we obtain results for one finger or actuator of the hand, showing the relationship between time and deformation.\u003c/p\u003e\n\u003ch2\u003eSimulation of Complete Hand\u003c/h2\u003e\n\u003cp\u003eAfter performing the simulation for a single finger, we proceed to simulate the entire hand. We precisely position each finger in the hand\u0026apos;s palm with accurate measurements. Following the same procedure as we did for a single finger, we define the material, import the STEP file, set boundaries, create the mesh, apply pressure, and define gravity.\u003c/p\u003e\n\u003cp\u003eUpon running the simulation for the complete hand, we obtain the following results:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo evaluate the design of the hand we checked its deformation behavior by applying pressure.\u003c/p\u003e\n\u003cp\u003eFirst, we generated a graph showing the relationship between pressure and deformation for the entire hand, illustrating how the hand deforms under applied pressure.\u003c/p\u003e\n\u003cp\u003eSecond, we obtain a graph showing the relationship between time and deformation, indicating the extent of deformation over a specific period.\u003c/p\u003e\n\u003cp\u003eThis comprehensive approach provides valuable insights into the behavior of both individual fingers and the entire hand under various conditions, making it easier to design and create a practical soft robotic hand.\u003c/p\u003e"},{"header":"METHODOLOGY","content":"\u003cp\u003eAs to the major objectives of our project we aimed at developing the prosthetic hand that should be lightweight, humanoid and comfortable to wear. The initial phase of the manufacturing process for this hand calls for a meticulous developmental process in SolidWorks with all dimensions and additional features inserted. That is followed by using this model as a mold to 3D print a different mold. Then another mold, which is a liquid silicone material, is then poured into the mold to dry and solidify to from the core of the hand. Finally, the prosthetic hand is built with the addition of a palm part designed for the specific user.\u003c/p\u003e\n\u003ch3\u003eWorking on the Mold for the Actuator\u0026nbsp;\u003c/h3\u003e\n\u003cp\u003e\u0026nbsp;It is most preferable that it looks like a human hand and hence the design of the hand is made to look as natural as possible for acceptability. This paper adopted the SolidWorks software to design a mold of the first designs of the soft pneumatic actuators. Thus, the dimensions of the actuator were designated as L = 82 mm, W = 20 mm, CL = 12 mm, CW = 5 mm, and H = 10 mm if the human finger size is quite average. This chamber has an interior hole of 7 mm and a hall with a square of 2 mm to get an idea of the tube size. To achieve these requirements, the 3D model of the actuator was modeled carefully in SolidWorks environment with the help of regular modeling tools like extrusion, loft, sweep and fillet. Finally, a base mold was created that should fit the tunnel and upper portions of the actuator, in size of 86 mm in length and 26 mm in width.\u003c/p\u003e\n\u003cp\u003eWorking on the Mold for the Actuator\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe two critical processes in the making of the soft pneumatic actuators involved choosing the right material and proper casting. Thus, to obtain the desired flexibility, we chose Ecoflex 00-30 silicone rubber. To make one finger actuator, 15 grams of the silicone rubber (half of which is A and the other half is B) on a cup should be mixed thoroughly for at least three minutes. Finally, the achieved blend was tapped to get rid of presence of air bubbles which were crucial to achieving the best performance. Subsequently, the mixture of silicon was then gradually introduced into the prepared mold so as to minimizes the formation of new bubbles. The solution of the silicone was then left for the recommended four hours to harden after the filling of the mould. Once the curing cycle had been completed, the finished actuator was removed from the mold on most of the MMC system, and using a sharp knife or scissors No. 11, the excess rubber was finally trimmed to give the actuator a neat surface.\u003c/p\u003e\n\u003ch3\u003eDesigning the Palm\u003c/h3\u003e\n\u003cp\u003eSeveral factors affect the usability and functionality of the soft pneumatic hand, including the palm. Concerning design, the gloves\u0026rsquo; flexibility and comfort, as well as the way they fit various hand sizes and shapes were well mastered. In a bid of designing a hand that produces movements like those of a real palm, thus physical analysis on the palm of the human hand was conducted initially. To ensure they could receive the gloves and feel that they were truly comfortable, more variables such as the general length of fingers, space between the fingers, and range of motion of the fingers were considered.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The first model created following the design was the cardboard model, which made it easier and cheaper to test on. The cardboard designed for minor changes and adjustments, provided the basic usability, comfort, and feasibility of the palm. Their shape, size, and all the considerable features might then be adjusted because there is an opportunity to use the CAD software to create the most accurate vision of what the hand will look like. The design was made even better particularly using expertise and user feedback. Last, 3D printing or molding procedures were applied to convert the final stage of the virtual model into tangible prototype. The actual palm was also tested through various experiments in this process to ensure that scores of performances ideal for a human like palm were achieved and tested in terms of gripping, grasping and overall ability to move things in a way in a human-like manner. Another method that involved relating feedback from users and the ergonomic assessments were made to effect changes.\u003c/p\u003e\n\u003ch3\u003eIntegrating the Fingers with the Palm\u003c/h3\u003e\n\u003cp\u003eAs the final step, incorporating the completed soft pneumatic fingers to the palm was done. For the fingers to fit properly the fingers were inserted properly into the palm mold which was developed uniquely. After that, Ecoflex-30 silicone was carefully poured into the mold, fulfilling two vital purposes: After that, Ecoflex-30 silicone was carefully poured into the mold, fulfilling two vital purposes:\u003c/p\u003e\n\u003cp\u003e1. \u0026nbsp; \u003cstrong\u003eSupport Structure\u003c/strong\u003e: The Eco flex provided a strong internal structure to hold the fingers in place within the palm, maintaining their proper alignment during movement.\u003c/p\u003e\n\u003cp\u003e2. \u0026nbsp; \u003cstrong\u003eSoft and Compliant Palm\u003c/strong\u003e: The Eco flex created a soft and flexible palm, enhancing the hand\u0026apos;s safety when interacting with objects and surfaces.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The pouring process demanded precision to ensure complete filling of the mold. Once filled, the Eco flex cured and solidified, permanently integrating the fingers with the palm and completing the fabrication of the soft pneumatic hand.\u003c/p\u003e\n\u003ch2\u003eControl System\u003c/h2\u003e\n\u003cp\u003eA prosthetic hand must interact closely with the human body to be a useful artificial organ, and its control must be as instinctive and natural as possible. The soft pneumatic actuator in this study was precisely and accurately actuated by the pneumatic control system that was designed for it. It was made up of two pneumatic pumps that produced the required pressure for actuation: one for positive pressure and another for negative pressure. The solenoid valves that controlled the pumps\u0026apos; opening and closing were attached to these pumps. After that, the system-controlled airflow using a five-channel air distribution manifold, each of which was linked to a separate solenoid valve that controlled the amount of air that reached each finger.\u003c/p\u003e\n\u003cp\u003eA general layout of the pneumatic system has been illustrated in the Fig.4.2.\u003c/p\u003e\n\u003cp\u003eFirst module was made up of two solenoid-valves directly controlling the positive and negative pressures of the compressed air. These valves are all about the quick and accurate pressure management that delivers the best actuator performance possible. Five solenoid valves were included in the second module; one for finger movement and deformation of each one. As it would later be seen, each finger was connected to these actuators and this allowed independent control of each, thereby offering the ability to move and manipulate.\u003c/p\u003e\n\u003cp\u003eA basic Arduino microcontroller motor driver was integrated into this pneumatic control system and it was a customized to give precise and timely strokes for the actuators with proper duration on the valves. The DC supply that was responsible for the microcontroller allowed the system to have all the power it required to operate. In this way the movements of the prosthetic hand were highly controlled and efficiently mimicked an actual human hand.\u003c/p\u003e\n\u003ch2\u003e\u0026nbsp;4.3 User Interface Application\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003e\u0026nbsp;A user interface application was developed using the Visual Studio so as to make controlling of the soft pneumatic actuator easier. The given program provided a GUI interface possessed for controlling the actuator in real time. The software was very simple and more importantly, intuitive which allowed the users to dictate how the actuator should move. Concerning the mode of handling objects and performing various tasks such as rehabilitation besides gripping and handling objects like bottles as well as balls etc., options were supplied within the interface. The GUI has input boxes for setting the grip force for activities such as holding a bottle and the time for which it should release the bottle, along with the start/stop buttons.\u003c/p\u003e\n\u003cp\u003eUsers could input the degree of grip they wished to have before starting the action and the time of engagement before the structure released. This was helpful to the user because it meant that instead of the actuator determining the hand movement patterns and postures the user could program it to assume any desired hand positions. This way, the possibilities of the software being tested were discovered along with the fact that it allows the soft pneumatic actuator to be tested in various circumstances without any difficulty.\u003c/p\u003e\n\u003cp\u003eIt interfaced the application with the motor driver Arduino microcontroller through a serial\u0026nbsp;communication port for real-time control of the pneumatic control system regarding the actuator movement.\u003c/p\u003e\n\u003cp\u003eAfter considering all the parameters we realized that, the creation and testing of the soft pneumatic actuator relied heavily on the user interface application. It made it simple for users to experiment with various actuation patterns and combinations by enabling accurate and effective control. The straightforward design and extensive control options of the app enabled this full testing and evaluation of the actuator\u0026apos;s capabilities.\u003c/p\u003e\n\u003ch2\u003e4.4 Fabrication of Pressure Sensor\u003c/h2\u003e\n\u003cp\u003eInitially, 3D molds measuring 60 x 10 mm with a thickness of 1.25 mm were designed using SolidWorks 2016 and produced with an UltiMaker 3D printer and Cura software. A digital scale with a precision of 0.001g was employed to measure graphene Nano-powder, which had a thickness of 5-20 nm and an area size of 10 x 10 \u0026micro;m. The graphene weighed 16 mg.\u003c/p\u003e\n\u003cp\u003eThe graphene powder was thoroughly mixed with Ecoflex-0030, a silicone rubber provided in two parts (A and B) with a weight ratio of 1:1. This mixture was poured into the 3D-printed mold. The homogeneous Eco flex/Graphene blend could cure for 4 hours, resulting in a thin film of \u0026nbsp; Eco-flex/Graphene composite.\u003c/p\u003e\n\u003cp\u003eAfter curing, very thin layer of Ecoflex/Graphane was located between two copper (Cu) electrodes in order to produce high sensitive sensor base. It was then connected to the soft actuator of the hand as a sensor to read the data collected. These actuators were used to come up with a pneumatic hand for the disabled persons due to various physical impairments. The entire process is depicted in the following Fig. 4.5\u003c/p\u003e"},{"header":"RESULTS AND DISCUSSION","content":"\u003cp\u003eThe effectiveness of the developed soft robotic hand was demonstrated for several tasks that simulate gripping and holding tasks of the human hand. These activities included handling or picking up small and large objects, lifting weights and handling delicate items. The compliance and flexibility of the soft robotic hand proved to be useful for manipulation of objects of varying form and size since this simplifies the interaction of the tool with the surrounding environment for multiple purposes.\u003c/p\u003e\n\u003ch2\u003eTasks performed by Hand Robot\u0026nbsp;\u003c/h2\u003e\n\u003ch3\u003eGrasping Task\u003c/h3\u003e\n\u003cp\u003eThe grasping task was demonstrated by the soft robotic hand picking up objects of various dimensions including a bottle, a ball and some of the objects that are used in rehabilitation activities. The affectation of the hand provided the slippery objects to be gripped accurately and securely and the pneumatic actuated fingers of the hand were able to enclose the objects in their fingers and hold objects steady if the objects were tilted or rotated. The skin layer of the hand being soft and somewhat malleable in consistency ensured that the objects did not slide off and the user had a good grasp on the objects.\u003c/p\u003e\n\u003ch3\u003eLifting Task\u003c/h3\u003e\n\u003cp\u003eThe lifting task included the soft robotic hand lifting loads of various quantities and types for example a small load and a large load. Previously, the hand took the two types of weights and exerted significant force to lift them, proving its steadiness. With help of pneumatic actuation, the hand could regulate its force depending on the weight of the object and it would not slip or drop the object.\u003c/p\u003e\n\u003ch3\u003eManipulation Task\u003c/h3\u003e\n\u003cp\u003eThe manipulation task included using the soft robotic hand to pick up objects such as a piece of paper and foam ball. The outer layer of the hand is fleshy which disables it from becoming deformed by the nature of the object to be held as is the case with the mechanical hand. Thus, using the pneumatic actuation system the hand was sufficiently precise to place the necessary pressure on the object, without applying the damaging force.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Evaluated on performance and analyzed statistically, the study demonstrated that the soft robotic hand was very reliable when it was used on different trials. The hand’s functionality and dexterity also meant that it was versatile in handling various sizes and shapes of the object, thus positively impacting the capabilities of the given individual to do many routine activities. Due to its lightweight and relatively cheap to produce, the soft robotic hand could be a viable solution for people in developing countries who are unable to gain access to highly technical prosthetic limbs.\u003c/p\u003e\n\u003ch2\u003eCharacterization of Pneumatic System\u003c/h2\u003e\n\u003cp\u003eThe functionalities of a prosthetic hand as a superior artificial limb depend on its interaction with the human body where such aspects as control system must be made natural. Regarding the control, a pneumatic control system was used in this work with objective of accurately controlling the soft pneumatic actuator to help improve the prosthetic hand advanced performance.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;To attain fine and stable control of the soft pneumatic actuator, the control system was interfaced with an Arduino micro controller. This microcontroller was used in regulating the time and period of validity of valves. The system could have a capacity of a pressure range of 400-650 mmHg which in Pascal is equivalent to 53. 23 to 86. 65. In addition, the negative pressure can be varied up to a maximum of the 46. 66 Pascal for the procedure.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The applied pressure allowed the sizes of the pneumatic chambers to increase, which in its turn allowed the fingers to extend and open.\u003c/p\u003e\n\u003ch2\u003eGUI to Control our Pneumatic System\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eTO control the soft pneumatic hand, the user interface application which was designed in Visual Studio and Tkinter was created. Python combined with GUI library called Tkinter is the best option to develop the graphical interface for Arduino solutions. Tkinter is the standard GUI library for Python supporting developing the efficient and simple interfaces. For the Game application, this use-case let users have a GUI of the actuator where they interact with the movements of the actuator in real-time. The app included nine possibilities of creating different pliages of the hand which allowed the user to control the actuator to obtain a desired hand form.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Results of the experiments confirm that the soft pneumatic actuator is capable of fine grasping and manipulation in its tasks that require pick up small object and manipulate it. Doing these jobs, the actuator was able to perform with lots of precision and the result was constant which made it clear that it is so versatile that it can work in different tasks.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Thus, the results of the study indicate that it is possible to develop, manufacture and control a soft pneumatic actuator to be incorporated into a robotic hand. Thanks to the precise control achievable by means of the control system and the user interface application and the flexibility and low weight of the actuator, this technology may be applied in various fields, namely robotics, manufacturing, and healthcare.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;All in all, the soft robotic hand that is featured in this thesis is accurate and precise as stated by the evaluation of gripping tests and the holding experiment results. Due its compliance and versatility, it offered generalized adaption to the shaped and sized objects in the conventional daily usage. Opening the dozens of videos of people with hand disabilities, softly moving fingers of the robotic hand can dramatically change the lives of those individuals and make them freer\u003c/p\u003e"},{"header":"CONCLUSION AND FUTURE WORK","content":"\u003cp\u003eSubstantial advancements have been achieved in this thesis on the design, modeling and fabrication of soft robotic hands mainly in rehabilitation of individuals with paralysis because of strokes. This means that my thorough approach includes proper material selection of the arm contraption and its specific casting methods, so my current prosthetic hand is as light and mimics natural hand movements as much as the Hitec controlling mechanism allows.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Significantly, the literature review touched on the possibilities of soft robotic hands due to their safety, elasticity, and ability for safe interaction with people. It also made a call for proper rehabilitation procedures and aids for the disabled persons as well as for technology to be enhanced. In an attempt to enhance the effectiveness of soft robotic hands, we reviewed several systems and enhancements such as incorporation of Tactile sensing and Hybrid grasping system.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In the simulation chapter, we revisited how to do the actuator design in SolidWorks and prepare the STEP file from the design model for ANSYS software simulations. These simulations provided valuable information pertaining to the interaction and functionality of the hand as a single structure and each finger at different circumstances. The results lay the basis for the modification of the design and ensuring the functionality of the soft prosthetic hand. Some of the findings are general trends in deformation and relationship between pressure, time, and deformation.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The fabrication process of the hand described in the methodology chapter was the way in which the mold of the actuator was made to the joining of the fingers and the palm, inclusive. Due to the extremity of Eco-flex 00-30 silicone rubber and optimized casting techniques, soft pneumatic actuators similar to human finger motion have been developed. In addition, due to developing the application to the graphical user interface the real-time control of actuators was enabled while, by testing all actuators at once, assessing their potential was significantly improved.\u003c/p\u003e\n\u003cp\u003eAll things considered, our work shows that soft robotics can be used to develop efficient rehabilitation tools that can greatly improve the quality of life for people with hand problems. The potential of soft robotic hands in both rehabilitative and assistive applications is demonstrated by the integration of cutting-edge materials, exact production techniques, and cutting-edge control systems.\u003c/p\u003e\n\u003ch2\u003eFuture Work\u003c/h2\u003e\n\u003cp\u003eWhile this research has made substantial progress in the development of soft robotic hands, several areas warrant further exploration to enhance their functionality, scalability, and real-world applicability.\u003c/p\u003e\n\u003cp\u003eImprovement of Material Properties:More attention should be paid to the development of new materials or further enhancement of the existing ones that would contribute to increasing the toughness and efficiency of soft pneumatic actuators. The more durable and flexible materials are needed for the prolonged usage or frequent usage in the rehabilitative settings; the more responsive material should also be investigated for further application.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIntegration of Advanced AI Introducing:\u0026nbsp;more advanced AI models for improving the mechanization and automation of the soft robotic hands’ control systems would have great implications. Here several solutions are proposed: The ML algorithm could be used to fine-tune grip force and to predict patterns in the users’ movements, and to change as necessary depending on the task. This would allow the robotic hand to execute more detailed movements and change the exactness on how it is used first hand by the user.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Scalability and Robustness: The problems associated with the increase in size and reliability in real-life conditions should be solved to advance the embrace of soft robotic hands. The further researches should be aimed at creating the mass production techniques, as well as on the devices’ ability to function in real-life conditions, including its interaction with various climatic conditions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEnhanced Sensing Technologies:\u0026nbsp;Enhancement of the feedback mechanisms more advanced of tactile and pressure sensing technologies ascends the performance of soft robotic hands. Future innovation in sensors that yield better force distribution and object handling data in real time will improve the devices’ control and functions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUser-Centric Design and Testing:\u0026nbsp;This is because after the design process of soft robotic hands there is need for user feedback and ergonomic evaluations for the next design iteration. Trials with extensive users, that include people with different types and various degrees of hand impairment, will facilitate a better understanding of the real-life difficulties and preferable options.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePersonalized Rehabilitation Programs:\u0026nbsp;It is possible to state that the application of soft robotics in creating individual patient’s rehabilitation plan could be the effective means to improve the progress of the recovery. Such programs could employ AI techniques in the data handling processes to choreograph individualized exercises and monitor the improvement, thus offering a better and more enjoyable approach to rehabilitation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In this way, future research would be established based on the findings of this thesis to reveal more efficient, reliable and user friendly soft robotic hands that could positively transform the lives of people with hand disabilities.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eACKNOWLEDGEMENT\u003c/h2\u003e \u003cp\u003eThis undergraduate level final year project was supported by Pakistan Engineering Council.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eNational Institute of Child Health and Human Development, \u0026quot;Stroke Risk Factors,\u0026quot; National Institutes of Health, [Online]. Available: https://www.nichd.nih.gov/health/topics/stroke/conditioninfo/risk. 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[Accessed: Aug. 15, 2024].\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Sukkur IBA University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Soft Robotics, PneuNets, Stroke Rehabilitation, Additive Manufacturing, Wearable Robotic Hand","lastPublishedDoi":"10.21203/rs.3.rs-5812474/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5812474/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study focuses on the development of soft robotic hand designed to aid individuals with hand disabilities, particularly those paralyzed due to strokes. Globally, strokes affect 15 million people annually, leading to 5 million deaths and leaving another 5 million with permanent disabilities that significantly impact their lives and communities. The soft robotic hand developed attempts to addresses the limitations of traditional robotic hands through the use of PneuNets, a pneumatic network framework that mimics the structure and function of a human hand. The hand's design incorporates pneumatic chambers that enable controlled finger movements, essential for grasping, lifting, and manipulating objects with precision. The primary components of the hand were fabricated using additive manufacturing and molding techniques, with a silicone outer layer added to enhance safety and compliance. The microcontroller-based control system is tailored to execute desired actions effectively, ensuring the soft hand’s adaptability to various tasks. Performance evaluations involved both simple and complex task profiles, demonstrating the hand's capability to handle a variety of objects with low variability in force and high precision. Specific technical results include the measurement of grasping forces, pressure requirements for actuation, and the assessment of attenuation losses during operation. Prior designs of soft robotic hands often suffer from issues like single-mode gripping and high attenuation losses; our approach mitigates these challenges through an optimized mechanical design coupled with learning algorithms that enhance grasping and manipulation efficiency. The soft characteristics of the robotic hand allow it to adapt its shape, making it capable of handling objects of varying sizes and shapes, thereby improving the daily functionality for individuals with hand impairments. This novel design not only offers increased independence and quality of life for patients but also provides a cost-effective and easily producible solution for wearable soft robotics.\u003c/p\u003e","manuscriptTitle":"Design and Fabrication of Soft Prosthetic Hand","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-14 11:16:33","doi":"10.21203/rs.3.rs-5812474/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f2fc7614-e16c-4610-9a0b-d078273c7a56","owner":[],"postedDate":"January 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":42735070,"name":"Robotics"}],"tags":[],"updatedAt":"2025-01-14T11:16:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-14 11:16:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5812474","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5812474","identity":"rs-5812474","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}