Closing the Wearable Gap-Part IX: Validation of an Improved Ankle Motion Capture Wearable
Soft robotic sensors, a class of pliable, embeddable sensors, are well-suited for applications in wearable technology because of their ease of integration with common clothing articles. The suitability of soft robotic sensors for estimation of human joint angles has been proven; this research repres...
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| Veröffentlicht in: | IEEE access 2021, Vol.9, p.114022-114036 |
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| creator | Carroll, Will Turner, Alana Talegaonkar, Purva Parker, Erin Middleton, J. Carver Peranich, Preston Saucier, David Burch, Reuben F. Ball, John E. Smith, Brian K. Chander, Harish Knight, Adam C. Freeman, Charles E. |
| description | Soft robotic sensors, a class of pliable, embeddable sensors, are well-suited for applications in wearable technology because of their ease of integration with common clothing articles. The suitability of soft robotic sensors for estimation of human joint angles has been proven; this research represents another step towards development of a reliable laboratory data collection platform for the human ankle joint complex. In this research, the accuracy and repeatability of a newly-developed wearable prototype are evaluated as a potential replacement for camera-based motion capture by measuring differences between simultaneously collected motion capture and stretch sensor data. The accuracy of these measurements is compared to measurements collected using a previous prototype for validation. Results show that the newly-developed prototype is capable of joint angle estimation within 1.86° mean-absolute-error during complex, dynamic movements and that wearing shoes over the sock prototype does not significantly degrade performance. |
| doi_str_mv | 10.1109/ACCESS.2021.3102880 |
| format | Article |
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In this research, the accuracy and repeatability of a newly-developed wearable prototype are evaluated as a potential replacement for camera-based motion capture by measuring differences between simultaneously collected motion capture and stretch sensor data. The accuracy of these measurements is compared to measurements collected using a previous prototype for validation. Results show that the newly-developed prototype is capable of joint angle estimation within 1.86° mean-absolute-error during complex, dynamic movements and that wearing shoes over the sock prototype does not significantly degrade performance.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2021.3102880</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Biomechanics ; body sensor networks ; Capacitive sensors ; Data collection platforms ; Foot ; Footwear ; Legged locomotion ; Motion capture ; Performance degradation ; Prototypes ; Robot sensors ; Sensors ; Soft robotics ; stretch sensors ; wearable computers ; Wearable sensors ; Wearable technology</subject><ispartof>IEEE access, 2021, Vol.9, p.114022-114036</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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Results show that the newly-developed prototype is capable of joint angle estimation within 1.86° mean-absolute-error during complex, dynamic movements and that wearing shoes over the sock prototype does not significantly degrade performance.</description><subject>Biomechanics</subject><subject>body sensor networks</subject><subject>Capacitive sensors</subject><subject>Data collection platforms</subject><subject>Foot</subject><subject>Footwear</subject><subject>Legged locomotion</subject><subject>Motion capture</subject><subject>Performance degradation</subject><subject>Prototypes</subject><subject>Robot sensors</subject><subject>Sensors</subject><subject>Soft robotics</subject><subject>stretch sensors</subject><subject>wearable computers</subject><subject>Wearable sensors</subject><subject>Wearable technology</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNUdtKw0AQDaJgUb-gLws-p-4l2ez6VoKXQkXB-9My2UtNjdm6SQX_3m0j1XmZYeacMzOcJBkTPCEEy7NpWV7c308opmTCCKZC4L1kRAmXKcsZ3_9XHyYnXbfEMURs5cUoeS0b39XtAvVvFj1bCFA1Fl3BKr2D0KPZyzl6gqY20Ne-Rd4haNHsYxX8lzVo2r5H8I3fzkpY9evwJ3KcHDhoOnvym4-Sx8uLh_I6nd9ezcrpPNUZFn1qaJGBrqzT0hinqaFS8spRopmTghrJHLVVTJnDBIqiyBnjTBtHsHCOOHaUzAZd42GpVqH-gPCtPNRq2_BhoeIntW6sygAEp5kuiIDMCCcKERdxzTWpCp7TqHU6aMUHP9e269XSr0Mbz1c051TmWcZYRLEBpYPvumDdbivBamOJGixRG0vUryWRNR5YtbV2x5A5FkwK9gOfbIZf</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Carroll, Will</creator><creator>Turner, Alana</creator><creator>Talegaonkar, Purva</creator><creator>Parker, Erin</creator><creator>Middleton, J. 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| source | IEEE Open Access Journals; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals |
| subjects | Biomechanics body sensor networks Capacitive sensors Data collection platforms Foot Footwear Legged locomotion Motion capture Performance degradation Prototypes Robot sensors Sensors Soft robotics stretch sensors wearable computers Wearable sensors Wearable technology |
| title | Closing the Wearable Gap-Part IX: Validation of an Improved Ankle Motion Capture Wearable |
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