Closing the Wearable Gap-Part VII: A Retrospective of Stretch Sensor Tool Kit Development for Benchmark Testing
This paper presents a retrospective of the benchmark testing methodologies developed and accumulated into the stretch sensor tool kit (SSTK) by the research team during the Closing the Wearable Gap series of studies. The techniques developed to validate stretchable soft robotic sensors (SRS) as a me...
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creator | Talegaonkar, Purva Saucier, David Carroll, Will Peranich, Preston Parker, Erin Middleton, Carver Davarzani, Samaneh Turner, Alana Persons, Karen Casey, Landon Burch V, Reuben F. Ball, John E. Chander, Harish Knight, Adam Luczak, Tony Smith, Brian K. Prabhu, R. K. |
description | This paper presents a retrospective of the benchmark testing methodologies developed and accumulated into the stretch sensor tool kit (SSTK) by the research team during the Closing the Wearable Gap series of studies. The techniques developed to validate stretchable soft robotic sensors (SRS) as a means for collecting human kinetic and kinematic data at the foot-ankle complex and at the wrist are reviewed. Lessons learned from past experiments are addressed, as well as what comprises the current SSTK based on what the researchers learned over the course of multiple studies. Three core components of the SSTK are featured: (a) material testing tools, (b) data analysis software, and (c) data collection devices. Results collected indicate that the stretch sensors are a viable means for predicting kinematic data based on the most recent gait analysis study conducted by the researchers (average root mean squared error or RMSE = 3.63°). With the aid of SSTK defined in this study summary and shared with the academic community on GitHub, researchers will be able to undergo more rigorous validation methodologies of SRS validation. A summary of the current state of the SSTK is detailed and includes insight into upcoming experiments that will utilize more sophisticated techniques for fatigue testing and gait analysis, utilizing SRS as the data collection solution. |
doi_str_mv | 10.3390/electronics9091457 |
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Three core components of the SSTK are featured: (a) material testing tools, (b) data analysis software, and (c) data collection devices. Results collected indicate that the stretch sensors are a viable means for predicting kinematic data based on the most recent gait analysis study conducted by the researchers (average root mean squared error or RMSE = 3.63°). With the aid of SSTK defined in this study summary and shared with the academic community on GitHub, researchers will be able to undergo more rigorous validation methodologies of SRS validation. A summary of the current state of the SSTK is detailed and includes insight into upcoming experiments that will utilize more sophisticated techniques for fatigue testing and gait analysis, utilizing SRS as the data collection solution.</description><identifier>ISSN: 2079-9292</identifier><identifier>EISSN: 2079-9292</identifier><identifier>DOI: 10.3390/electronics9091457</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Ankle ; Athletes ; Benchmarks ; Biomechanics ; Coaches & managers ; Data analysis ; Data collection ; Electronic devices ; Fatigue tests ; Feedback ; Gait ; Human mechanics ; Laboratories ; Motion capture ; R&D ; Rehabilitation ; Research & development ; Researchers ; Robot sensors ; Root-mean-square errors ; Sensors ; Software ; Textiles ; Toolkits ; Wearable technology ; Wrist</subject><ispartof>Electronics (Basel), 2020-09, Vol.9 (9), p.1457</ispartof><rights>2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). 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K.</creatorcontrib><title>Closing the Wearable Gap-Part VII: A Retrospective of Stretch Sensor Tool Kit Development for Benchmark Testing</title><title>Electronics (Basel)</title><description>This paper presents a retrospective of the benchmark testing methodologies developed and accumulated into the stretch sensor tool kit (SSTK) by the research team during the Closing the Wearable Gap series of studies. The techniques developed to validate stretchable soft robotic sensors (SRS) as a means for collecting human kinetic and kinematic data at the foot-ankle complex and at the wrist are reviewed. Lessons learned from past experiments are addressed, as well as what comprises the current SSTK based on what the researchers learned over the course of multiple studies. Three core components of the SSTK are featured: (a) material testing tools, (b) data analysis software, and (c) data collection devices. Results collected indicate that the stretch sensors are a viable means for predicting kinematic data based on the most recent gait analysis study conducted by the researchers (average root mean squared error or RMSE = 3.63°). With the aid of SSTK defined in this study summary and shared with the academic community on GitHub, researchers will be able to undergo more rigorous validation methodologies of SRS validation. A summary of the current state of the SSTK is detailed and includes insight into upcoming experiments that will utilize more sophisticated techniques for fatigue testing and gait analysis, utilizing SRS as the data collection solution.</description><subject>Ankle</subject><subject>Athletes</subject><subject>Benchmarks</subject><subject>Biomechanics</subject><subject>Coaches & managers</subject><subject>Data analysis</subject><subject>Data collection</subject><subject>Electronic devices</subject><subject>Fatigue tests</subject><subject>Feedback</subject><subject>Gait</subject><subject>Human mechanics</subject><subject>Laboratories</subject><subject>Motion capture</subject><subject>R&D</subject><subject>Rehabilitation</subject><subject>Research & development</subject><subject>Researchers</subject><subject>Robot sensors</subject><subject>Root-mean-square errors</subject><subject>Sensors</subject><subject>Software</subject><subject>Textiles</subject><subject>Toolkits</subject><subject>Wearable technology</subject><subject>Wrist</subject><issn>2079-9292</issn><issn>2079-9292</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNplUMtOwzAQtBBIVKU_wGklzgE_kibmVgqUikogWuAYuc6apqRxsN1K_D2uygGJveyudjSzM4ScM3ophKRX2KAOzra19pJKlmb5EelxmstEcsmP_8ynZOD9msaSTBSC9ogdN9bX7QeEFcI7KqeWDcJEdcmzcgHeptNrGMELRn7fRZl6h2ANzIPDoFcwx9ZbBwtrG3isA9ziDhvbbbANYOLhBlu92ij3CQv0IeqckROjGo-D394nr_d3i_FDMnuaTMejWaIFkyExecYpz5Z5VRnNuI47lXKY6lREe-lyKIqKKqaNVKxgtFKMZgypElmR5kMhRJ9cHHg7Z7-2Ubtc261ro2TJ05Ttc8pkRPEDSkd73qEpO1fHd79LRst9tuX_bMUPr19uxA</recordid><startdate>20200901</startdate><enddate>20200901</enddate><creator>Talegaonkar, Purva</creator><creator>Saucier, David</creator><creator>Carroll, Will</creator><creator>Peranich, Preston</creator><creator>Parker, Erin</creator><creator>Middleton, Carver</creator><creator>Davarzani, Samaneh</creator><creator>Turner, Alana</creator><creator>Persons, Karen</creator><creator>Casey, Landon</creator><creator>Burch V, Reuben F.</creator><creator>Ball, John E.</creator><creator>Chander, Harish</creator><creator>Knight, Adam</creator><creator>Luczak, Tony</creator><creator>Smith, Brian K.</creator><creator>Prabhu, R. 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subjects | Ankle Athletes Benchmarks Biomechanics Coaches & managers Data analysis Data collection Electronic devices Fatigue tests Feedback Gait Human mechanics Laboratories Motion capture R&D Rehabilitation Research & development Researchers Robot sensors Root-mean-square errors Sensors Software Textiles Toolkits Wearable technology Wrist |
title | Closing the Wearable Gap-Part VII: A Retrospective of Stretch Sensor Tool Kit Development for Benchmark Testing |
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