Sudden stop detection and automatic seating support with neural stimulation during manual wheelchair propulsion

Abstract

Objective: Wheelchair safety is of great importance since falls from wheelchairs are prevalent and often have devastating consequences. We developed an automatic system to detect destabilizing events during wheelchair propulsion under real-world conditions and trigger neural stimulation to stiffen the trunk to maintain seated postures of users with paralysis.Design: Cross-over interventionSetting: Laboratory and community settingsParticipants: Three able-bodied subjects and three individuals with SCI with previously implanted neurostimulation systemsInterventions: An algorithm to detect wheelchair sudden stops was developed. This was used to randomly trigger trunk extensor stimulation during sudden stops eventsOutcome Measures: Algorithm success and false positive rates were determined. SCI users rated each condition on a seven-point Usability Rating Scale to indicate safety.Results: The system detected sudden stops with a success rate of over 93% in community settings. When used to trigger trunk neurostimulation to ensure stability, the implant recipients consistently reported feeling safer (P<.05 for 2/3 subjects) with the system while encountering sudden stops as indicated by a 1-3 point change in safety rating.Conclusion: These preliminary results suggest that this system could monitor wheelchair activity and only apply stabilizing neurostimulation when appropriate to maintain posture. Larger scale, unsupervised and longer-term trials at home and in the community are indicated. This system could be generalized and applied to individuals without an implanted stimulation by utilizing surface stimulation, or by actuating a mechanical restraint when necessary, thus allowing unrestricted trunk movements and only restraining the user when necessary to ensure safety.Trial Registration: NCT01474148.

Keywords: Electrical stimulation; Mobility; Safety; Spinal cord injury; Wheelchairs.

Figures

Figure 1

Wheelchair with wireless IMU affixed to rear axle (lid removed for picture).

Figure 2

Block diagram of algorithm used to process acceleration signals and detect sudden stops.

Figure 3

Plots of the RMS and derivative of the RMS during typical trials of two different conditions. The blue trace is a crash condition, which activated once the RMS and derivative signals crossed their respective thresholds. The red trace is an over-ground trial (no collision) traveling over a brick sidewalk. The activation thresholds are represented by the horizontal lines and the vertical dashed line indicates the time of the collision during that trial.

Figure 4

AB subject performing a sudden stop event (lodging castor into pothole).

Figure 5

Subject with SCI propelling over various terrains with algorithm active.