Closing the Wearable Gap—Part III: Use of Stretch Sensors in Detecting Ankle Joint Kinematics During Unexpected and Expected Slip and Trip Perturbations

Electronics

R.K. Prabhu¹  BrianK. Smith²  ReubenF. Burch V²  Tony Luczak²  Harish Chander³  Ethan Stewart³  AdamC. Knight³  Phuoc Nguyen⁴  JohnE. Ball⁴  David Saucier⁴ 

[1] Department of Agricultural and Biomedical Engineering, Mississippi State University, Mississippi State, MS 39762, USA;Department of Industrial Systems Engineering, Mississippi State University, Mississippi State, MS 39762, USA;Department of Kinesiology, Mississippi State University, Mississippi State, MS 39762, USA;Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS 39762, USA;

关键词: falls;    slips;    trips;    postural perturbations;    wearables;    stretch-sensors;    ankle kinematics;   

DOI  :  10.3390/electronics8101083

来源: DOAJ

【 摘 要 】

Background: An induced loss of balance resulting from a postural perturbation has been reported as the primary source for postural instability leading to falls. Hence; early detection of postural instability with novel wearable sensor-based measures may aid in reducing falls and fall-related injuries. The purpose of the study was to validate the use of a stretchable soft robotic sensor (SRS) to detect ankle joint kinematics during both unexpected and expected slip and trip perturbations. Methods: Ten participants (age: 23.7 ± 3.13 years; height: 170.47 ± 8.21 cm; mass: 82.86 ± 23.4 kg) experienced a counterbalanced exposure of an unexpected slip, an unexpected trip, an expected slip, and an expected trip using treadmill perturbations. Ankle joint kinematics for dorsiflexion and plantarflexion were quantified using three-dimensional (3D) motion capture through changes in ankle joint range of motion and using the SRS through changes in capacitance when stretched due to ankle movements during the perturbations. Results: A greater R-squared and lower root mean square error in the linear regression model was observed in comparing ankle joint kinematics data from motion capture with stretch sensors. Conclusions: Results from the study demonstrated that 71.25% of the trials exhibited a minimal error of less than 4.0 degrees difference from the motion capture system and a greater than 0.60 R-squared value in the linear model; suggesting a moderate to high accuracy and minimal errors in comparing SRS to a motion capture system. Findings indicate that the stretch sensors could be a feasible option in detecting ankle joint kinematics during slips and trips.

【 授权许可】

Unknown