Abstract
| Language | English |
|---|---|
| Pages | 523-527 |
| Journal | Gait & Posture |
| Volume | 30 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2009 |
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Real-time gait event detection using wearable sensors. / Hanlon, Michael; Anderson, Ross.
In: Gait & Posture, Vol. 30, No. 4, 2009, p. 523-527.Research output: Contribution to journal › Article
TY - JOUR
T1 - Real-time gait event detection using wearable sensors
AU - Hanlon, Michael
AU - Anderson, Ross
PY - 2009
Y1 - 2009
N2 - Real-time gait event detection is a requirement for functional electrical stimulation and gait biofeedback. This gait event detection should ideally be achieved using an ambulatory system of durable, lightweight, low-cost sensors. Previous research has reported issues with durability in footswitch systems. Therefore, this study describes the development and assessment of novel detection algorithms using footswitch and accelerometer sensors on twelve healthy individuals. Subjects were equipped with one force sensitive resistor on the heel, one accelerometer at the foot, and one accelerometer at the knee. Subjects performed ten 8-m walking trials in each of three conditions: normal, slow, and altered (reduced knee ROM) walking. Data from a subset of four subjects were used to develop prediction algorithms for initial contact (IC). Subsequently, these algorithms were tested on the remaining eight subjects against standard forceplate IC data (threshold of 5 N on a rising edge). The footswitch force threshold algorithm was most accurate for IC detection (mean absolute error of 2.4±2.1 ms) and was significantly more accurate (p
AB - Real-time gait event detection is a requirement for functional electrical stimulation and gait biofeedback. This gait event detection should ideally be achieved using an ambulatory system of durable, lightweight, low-cost sensors. Previous research has reported issues with durability in footswitch systems. Therefore, this study describes the development and assessment of novel detection algorithms using footswitch and accelerometer sensors on twelve healthy individuals. Subjects were equipped with one force sensitive resistor on the heel, one accelerometer at the foot, and one accelerometer at the knee. Subjects performed ten 8-m walking trials in each of three conditions: normal, slow, and altered (reduced knee ROM) walking. Data from a subset of four subjects were used to develop prediction algorithms for initial contact (IC). Subsequently, these algorithms were tested on the remaining eight subjects against standard forceplate IC data (threshold of 5 N on a rising edge). The footswitch force threshold algorithm was most accurate for IC detection (mean absolute error of 2.4±2.1 ms) and was significantly more accurate (p
U2 - 10.1016/j.gaitpost.2009.07.128
DO - 10.1016/j.gaitpost.2009.07.128
M3 - Article
VL - 30
SP - 523
EP - 527
JO - GAIT and POSTURE
T2 - GAIT and POSTURE
JF - GAIT and POSTURE
SN - 0966-6362
IS - 4
ER -