Detecting destabilizing wheelchair conditions for maintaining seated posture

Abstract

Purpose The purpose of this study was to detect and classify potentially destabilizing conditions encountered by manual wheelchair users with spinal cord injuries (SCI) to dynamically increase stability and prevent falls. Methods A volunteer with motor complete T11 paraplegia repeatedly propelled his manual wheelchair over level ground and simulated destabilizing conditions including sudden stops, bumps and rough terrain. Wireless inertial measurement units attached to the wheelchair frame and his sternum recorded associated accelerations and angular velocities. Algorithms based on mean, standard deviation and minimum Mahalanobis distance between conditions were constructed and applied to the data off-line to discriminate between events. Classification accuracy was computed to assess effects of sensor position and potential for automatically selecting a dynamic intervention to best stabilize the wheelchair user. Results The decision algorithm based on acceleration signals successfully differentiated destabilizing conditions and level over-ground propulsion with classification accuracies of 95.8, 58.3 and 91.7% for the chest, wheelchair and both sensors, respectively. Conclusion Mahalanobis distance classification based on trunk accelerations is a feasible method for detecting destabilizing events encountered by wheelchair users and may serve as an effective trigger for protective interventions. Incorporating data from wheelchair-mounted sensors decreases the false negative rate.

Trunk Stability Enabled by Noninvasive Spinal Electrical Stimulation after Spinal Cord Injury

“…3,4 Individuals with SCI are consequently exposed to a higher risk of instability and falling even in a quiet seated posture, increasing the probability of fall-related pain, bone fractures, and other injuries. 5,6 In addition to restoring seated quiet and dynamic abilities, 7 clinical and physiological benefits of improving trunk posture and control have been shown to include a decrease in neck and back pain, 8,9 the ability to perform pressure relief, 10 improvements in bimanual workspace, 4 pelvic tilt, lateral vertebral alignment, 11,12 enhanced forward reaching and active pulling, 4,11 and improvements in diaphragmatic and deep breathing. 13 Hence, reaching an optimal level of quiet and dynamic seated postural capability is generally one of the key objectives in SCI rehabilitation, with the ultimate goal of enhancing affected individuals' health as well as performance and independence in daily activities.…”

Towards a Wearable Wheelchair Monitor: Classification of Push Style Based on Inertial Sensors at Multiple Upper Limb Locations

“…The use of inertial sensors has been examined in response to the rising interest in quantifying movement in wheelchair users for monitoring and rehabilitation purposes, due to their size, inexpensiveness and the fact that are not bound to a clinical setting [10]. For example, accelerometers have been used to measure basic parameters such as bouts of mobility by Sonemblum et al [11] and to record more complex tasks which can then be combined with classifying algorithms to distinguish between wheelchair activities [12] or recognise wheelchair destabilizing conditions [13]. Less attention has been given to measuring stroke patterns with wearable sensors.…”