An FBG Tactile Sensor Array and Self-SupervisedContrastive Learning Transformer for TumorDepth Estimation in Robotic Palpation

An FBG Tactile Sensor Array and Self-SupervisedContrastive Learning Transformer for TumorDepth Estimation in Robotic Palpation | 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 Article An FBG Tactile Sensor Array and Self-SupervisedContrastive Learning Transformer for TumorDepth Estimation in Robotic Palpation Shiyuan Dong, Peibo Sun, Jianrong Cai, Aoji Zhu, Zhenning Zhou, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9278913/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Restoring haptic feedback remains a major challenge in robot-assisted minimally invasive surgery (RMIS), especially for localizing subsurface tumors and estimating their depth. This paper presents a compact, high-density tactile sensor array based on fiber Bragg grating (FBG) sensing for robotic palpation. The array uses a honeycomb topology to increase spatial sampling within an 8.5 mm footprint while preserving high sensitivity. Static and dynamic tests show a linear force-wavelength response across seven channels, an average force resolution of 8.43 mN, and \((<)\) 1% full-scale dynamic error. To estimate tumor depth from palpation signals, we propose FBG-PatchFormer. Since depth annotations are scarce and costly to obtain, FBG-PatchFormer leverages contrastive self-supervised pretraining on unlabeled palpation windows to reduce the reliance on dense labels, and is then finetuned for depth classification. On phantom palpation with embedded inclusions, FBG-PatchFormer achieves 99.60% record-level accuracy on a ten-class depth task (blank and 2--10 mm). In vivo tests on porcine liver further demonstrate robust tumor localization under physiological motion and fluid interference, supporting the clinical potential of the proposed sensing system. Biological sciences/Cancer Physical sciences/Engineering Physical sciences/Mathematics and computing Health sciences/Oncology Fiber Bragg grating sensor array robotic palpation time-series transformer tumor depth estimation Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 05 May, 2026 Reviews received at journal 04 May, 2026 Reviewers agreed at journal 04 May, 2026 Reviewers agreed at journal 30 Apr, 2026 Reviewers agreed at journal 16 Apr, 2026 Reviewers invited by journal 16 Apr, 2026 Editor assigned by journal 14 Apr, 2026 Submission checks completed at journal 02 Apr, 2026 First submitted to journal 31 Mar, 2026 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. 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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-9278913","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":626062397,"identity":"d5b43dd8-9628-442c-8d9d-915fad00a5e5","order_by":0,"name":"Shiyuan Dong","email":"","orcid":"","institution":"Shanghai Jiao Tong University","correspondingAuthor":false,"prefix":"","firstName":"Shiyuan","middleName":"","lastName":"Dong","suffix":""},{"id":626062398,"identity":"335397e6-0a95-4eac-bb76-de57d0088c7c","order_by":1,"name":"Peibo Sun","email":"","orcid":"","institution":"Shanghai Jiao Tong 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Robotics","twitterHandle":"@NaturePortfolio","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Fiber Bragg grating, sensor array, robotic palpation, time-series transformer, tumor depth estimation","lastPublishedDoi":"10.21203/rs.3.rs-9278913/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9278913/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRestoring haptic feedback remains a major challenge in robot-assisted minimally invasive surgery (RMIS), especially for localizing subsurface tumors and estimating their depth. This paper presents a compact, high-density tactile sensor array based on fiber Bragg grating (FBG) sensing for robotic palpation. The array uses a honeycomb topology to increase spatial sampling within an 8.5 mm footprint while preserving high sensitivity. Static and dynamic tests show a linear force-wavelength response across seven channels, an average force resolution of 8.43 mN, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\((\u0026lt;)\\)\u003c/span\u003e\u003c/span\u003e1% full-scale dynamic error. To estimate tumor depth from palpation signals, we propose FBG-PatchFormer. Since depth annotations are scarce and costly to obtain, FBG-PatchFormer leverages contrastive self-supervised pretraining on unlabeled palpation windows to reduce the reliance on dense labels, and is then finetuned for depth classification. On phantom palpation with embedded inclusions, FBG-PatchFormer achieves 99.60% record-level accuracy on a ten-class depth task (blank and 2--10 mm). In vivo tests on porcine liver further demonstrate robust tumor localization under physiological motion and fluid interference, supporting the clinical potential of the proposed sensing system.\u003c/p\u003e","manuscriptTitle":"An FBG Tactile Sensor Array and Self-SupervisedContrastive Learning Transformer for TumorDepth Estimation in Robotic Palpation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-23 03:59:20","doi":"10.21203/rs.3.rs-9278913/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-05T13:55:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T11:41:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"117429578223633047933998418760192140658","date":"2026-05-04T06:41:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"10337944469096326970164153951786065979","date":"2026-04-30T11:10:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"193497681196142626094049275974545656370","date":"2026-04-16T12:33:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-16T06:09:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-14T11:50:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-03T03:41:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Robotics","date":"2026-03-31T10:59:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-robotics","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjrobot","sideBox":"Learn more about [npj Robotics](http://www.nature.com/npjrobot/)","snPcode":"44182","submissionUrl":"https://mts-npjrobot.nature.com/cgi-bin/main.plex","title":"npj Robotics","twitterHandle":"@NaturePortfolio","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fdf80b5f-805d-42f7-9a5d-ddc77fbe0f73","owner":[],"postedDate":"April 23rd, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-05T13:55:52+00:00","index":20,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T11:41:30+00:00","index":19,"fulltext":""},{"type":"reviewerAgreed","content":"117429578223633047933998418760192140658","date":"2026-05-04T06:41:52+00:00","index":18,"fulltext":""},{"type":"reviewerAgreed","content":"10337944469096326970164153951786065979","date":"2026-04-30T11:10:50+00:00","index":17,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":66627518,"name":"Biological sciences/Cancer"},{"id":66627519,"name":"Physical sciences/Engineering"},{"id":66627520,"name":"Physical sciences/Mathematics and computing"},{"id":66627521,"name":"Health sciences/Oncology"}],"tags":[],"updatedAt":"2026-04-23T03:59:20+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-23 03:59:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9278913","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9278913","identity":"rs-9278913","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}