A novel portable sensor to monitor bodily positions and activities in transtibial prosthesis users. (October 2022)

• Record Type: Journal Article
• Authors: Mertens, Joseph C.; Brzostowski, Jacob T.; Vamos, Andrew; Allyn, Katheryn J.; Hafner, Brian J.; Friedly, Janna L.; DeGrasse, Nicholas S.; Ballesteros, Daniel; Krout, Adam; Larsen, Brian G.; Garbini, Joseph L.; Sanders, Joan E.
• Is Part Of: Clinical biomechanics. Volume 99(2022)
• Publication Date: 2022-10
• Subjects: Activity monitor -- Amputee -- Residual limb -- Socket fit -- Body sensor -- Outcome assessment -- Limb-socket interface -- Prosthetic socket -- Inductive sensing -- Magnetic target; ADA American Disabilities Act -- C Capacitor -- ECHO A data logger used for long-term monitoring -- IRB Institutional Review Board -- kΩ kilohm -- L Inductor -- LDC counts Signal output units for the WAFERs -- pf picofarad -- WAFER A custom flexible printed circuit board antenna used as the sensing element in the distance sensor; Biomechanics -- Periodicals; Osteopathic medicine -- Periodicals; Biomechanics -- Periodicals; Osteopathic Medicine -- Periodicals; 612.76
• DOI: 10.1016/j.clinbiomech.2022.105741
• Languages: English
• ISSNs: 0268-0033

Abstract

Abstract: Background: Step activity monitors provide insight into the amount of physical activity prosthesis users conduct but not how they use their prosthesis. The purpose of this research was to help fill this void by developing and testing a technology to monitor bodily position and type of activity. Methods: Thin inductive distance sensors were adhered to the insides of sockets of a small group of transtibial prosthesis users, two at proximal locations and two at distal locations. An in-lab structured protocol and a semi-structured out-of-lab protocol were video recorded, and then participants wore the sensing system for up to 7 days. A data processing algorithm was developed to identify sit, seated shift, stand, standing weight-shift, walk, partial doff, and non-use. Sensed distance data from the structured and semi-structured protocols were compared against the video data to characterize accuracy. Bodily positions and activities during take-home testing were tabulated to characterize participants' use of the prosthesis. Findings: Sit and walk detection accuracies were above 95% for all four participants tested. Stand detection accuracy was above 90% for three participants and 62.5% for one participant. The reduced accuracy may have been due to limited stand data from that participant. Step count was not proportional to active use time (sum of stand, walk, and standing weight-shift times). Interpretation: Step count may provide an incomplete picture of prosthesis use. Larger studies should be pursued to investigate how bodily position and type of activity may facilitate clinical decision-making and improve the lives of people with lower limb amputation. Highlights: Thin, flexible, lightweight distance sensors were placed inside transtibial sockets. Sit, seated shift, stand, standing weight-shift, walk, partial doff, and non-use were detected. Step count data did not well-reflect active use (stands + walks + standing weight-shifts). Participants who had the highest active use temporarily doffed the most often.