Smart sock alerts olderpeople to risk of falling TrentUni
The over-sock was used in a human trial as a proof-of-concept that a motion sensing E-yarn can be integrated into a garment and, in combination with a deep learning algorithm, detect falls. Each motion sensing E-yarn contained one commercially available IMU that measured acceleration in three axes and angular velocity in three dimensions. For the trial, 13 healthy women were recruited.
The structure of the fiber braid was tight around the micro-pod, and previous work exploring vibration transmission through yarns indicated that such a structure would have a negligible effect on the transmission of vibration []; hence, it was not expected that the yarn structure would influence the recorded motion data, provided that tight textile structures were utilized.
The E-yarn was then integrated into the over-sock. The over-sock was seamlessly knit using three yarns on a Stoll ADF 3 E7.2 knitting machine . The sock included a knitted channel for the E-yarn to be inserted as well as a small, knitted pocket for the hardware unit . The hardware used for the human trials consisted of a microcontroller and a small operating circuit that was based on a recommended circuit design provided by the MPU-6050 datasheet to ensure the proper function of the IMU.
Data was collected using the Arduino 1.8.9 software , at a 25 Hz sampling rate (informed by the pilot study and the literature [
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