Validity of consumer-grade activity monitor to identify manual wheelchair propulsion in standardized activities of daily living

Abstract

BackgroundHypoactive lifestyle contributes to the development of secondary complications and lower quality of life in wheelchair users. There is a need for objective and user-friendly physical activity monitors for wheelchair-dependent individuals in order to increase physical activity through self-monitoring, goal setting, and feedback provision.ObjectiveTo determine the validity of Activ8 Activity Monitors to 1) distinguish two classes of activities: independent wheelchair propulsion from other non-propulsive wheelchair-related activities 2) distinguish five wheelchair-related classes of activities differing by the movement intensity level: sitting in a wheelchair (hands may be moving but wheelchair remains stationary), maneuvering, and normal, high speed or assisted wheelchair propulsion.MethodsSixteen able-bodied individuals performed sixteen various standardized 60s-activities of daily living. Each participant was equipped with a set of two Activ8 Professional Activity Monitors, one at the right forearm and one at the right wheel. Task classification by the Active8 Monitors was validated using video recordings. For the overall agreement, sensitivity and positive predictive value, outcomes above 90% are considered excellent, between 70 and 90% good, and below 70% unsatisfactory.ResultsDivision in two classes resulted in overall agreement of 82.1%, sensitivity of 77.7% and positive predictive value of 78.2%. 84.5% of total duration of all tasks was classified identically by Activ8 and based on the video material. Division in five classes resulted in overall agreement of 56.6%, sensitivity of 52.8% and positive predictive value of 51.9%. 59.8% of total duration of all tasks was classified identically by Activ8 and based on the video material.ConclusionsActiv8 system proved to be suitable for distinguishing between active wheelchair propulsion and other non-propulsive wheelchair-related activities. The ability of the current system and algorithms to distinguish five various wheelchair-related activities is unsatisfactory.

Motor learning outcomes of handrim wheelchair propulsion during active spinal cord injury rehabilitation in comparison with experienced wheelchair users

“…The vector counts were used to perform the classification. Classification was performed using custom-written Matlab algorithms, which were validated for detecting independent wheelchair propulsion [9]. Each epoch was classified either as independent wheelchair propulsion (propulsion as a result of arm power of the participant) or as other activity (including but not limited to: being pushed in the wheelchair, reaching movements, general upper body motions).…”

“…Each epoch was classified either as independent wheelchair propulsion (propulsion as a result of arm power of the participant) or as other activity (including but not limited to: being pushed in the wheelchair, reaching movements, general upper body motions). A given epoch was classified as independent wheelchair propulsion if the wheel counts were contained between 31 and 310 counts or if they exceeded 310 and at the same time wrist counts exceeded 98 [9]. In all other cases, an activity was classified as "other".…”

“…Mechanical efficiency in itself does not pinpoint where the change came from, therefore other factors that may influence the change in efficiency will be measured as well during the first and the last measurement moment (Figure 1). These factors will include: the cardiorespiratory and muscle function (increase in mechanical efficiency can be caused by an increase in overall physiological capacity) and the amount of independent wheelchair propulsion (amount of wheelchair propulsion practice may contribute to the rate of the learning process) [9]. Moreover, in order to show how the above-mentioned outcome measures relate to a commonly performed clinical measure, which is simple, cheap and easy to administer, the score on the wheelchair skill circuit will also be included [10].…”

Assessment of a markerless motion analysis system for manual wheelchair application

“…Inertial Measurement Units (IMUs) are easier to use, but, when wrist-applied as typical practice [ 4 ] lack detailed joint kinematics at the shoulder, a key joint in assessing injury risk for manual wheelchair users. Leving et al [ 5 ] has shown promise for IMUs to detect spatiotemporal parameters of motion, including activity level, but does not describe movement kinematics. Similarly, van der Slikke et al [ 6 – 9 ] have shown accurate measurements by IMUs in speed, displacement, and acceleration metrics applied to wheelchair sports.…”

Is Fitbit Charge 2 a feasible instrument to monitor daily physical activity and handbike training in persons with spinal cord injury? A pilot study

“…Their use during daily activities and training activities in particular is unpractical. Physical activity monitors were able to distinguish between active wheelchair propulsion and other nonpropulsive wheelchair-related activities in a laboratory setting [16]. Compliance in long-term use to monitor daily activities in free-living conditions, including training activities has been a problem in previous research on accelerometers, as well as activity monitors in behavioral change programs in people with SCI [17].…”