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Gait studies in sports and rehabilitation may benefit from online gait event detection algorithms for use in eventdependant feedback strategies. Event-dependant feedback systems may further benefit from durable, lightweight, low cost sensors for gait event detection. In this regard, this study describes the development and feasibility evaluation of an online gait event detection system using inertial sensor technology for the identification of Heel Strike (HS) and Toe Off (TO) events during treadmill running. Custom developed system software performs the online data acquisition, processing, graphical representations of lower extremity kinematics and online gait event detection. For increased robustness, a Finite State Controller architecture is employed for continuous detections of HS and TO during running. Pilot tests conducted with 7 healthy subjects during treadmill running verified the accuracy of gait event detection with mean timing errors of 14ms for HS and 27ms for TO compared to normative values. The effectiveness and robustness of gait event detection is promising signifying the use of the system for triggering event-dependant feedback during running gait retraining.

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Biofeedback systems have become a prominent component in the sports domain as a means of motor training and rehabilitation. This paper presents the development of a biofeedback prototype and system software framework facilitating its functionality in real time. The prototype incorporates an inertial measurement sensor unit, a wireless vibration stimulus module for vibrotactile biofeedback, and interactive system software behaving as the backbone of the system. The functionality of the prototype was tested with a stability test during which biofeedback was provided to improve postural control based on trunk tilt displacements. The test involved subjects standing in the tandem Romberg position during which their medial-lateral trunk tilt was measured, and postural sway biofeedback was conveyed via vibrotactile actuators placed on either side of the trunk. Two conditions were tested, namely eyes open and eyes closed, and postural sway with biofeedback was evaluated, as opposed to with no feedback. A 15.2 per cent sway reduction resulted in the eyes-open condition, and a significant reduction of 55.2 per cent was reported for the eyes-closed condition. The results demonstrate that instantaneous feedback provided via vibration stimulus can reduce postural sway based on trunk tilt measurements. Hence, the system's pertinence to comparable approaches employed in sports training and rehabilitation is foreseen.