Dataset Information

Accuracy and precision of consumer-level activity monitors for stroke detection during wheelchair propulsion and arm ergometry.

ABSTRACT: The purpose of this study was to evaluate whether consumer-level activity trackers can estimate wheelchair strokes and arm ergometer revolutions. Thirty able-bodied participants wore three consumer-level activity trackers (Garmin VivoFit, FitBit Flex, and Jawbone UP24) on the wrist. Participants propelled a wheelchair at fixed frequencies (30, 45 and 60 strokes per minute (spm)) three minutes each and at pre-determined varied frequencies, (30-80 spm) for two minutes. Participants also freely wheeled through an obstacle course. 10 other participants performed arm-ergometry at 40, 60 and 80 revolutions per minute (rpm), for three minutes each. Mean percentage error (MPE(SD)) for 30 spm were ?46(26)% for all monitors, and declined to 3-6(2-7)% at 60 spm. For the obstacle course, MPE ranged from 12-17(7-13)% for all trackers. For arm-ergometry, MPE was at 1-96(0-37)% with the best measurement for the Fitbit at 60 and 80 rpm, and the Garmin at 80rpm, with MPE = 1(0-1)%. The consumer-level wrist-worn activity trackers we tested have higher accuracy/precision at higher movement frequencies but perform poorly at lower frequencies.

SUBMITTER: Kressler J

PROVIDER: S-EPMC5812573 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Accuracy and precision of consumer-level activity monitors for stroke detection during wheelchair propulsion and arm ergometry.

Kressler Jochen J Koeplin-Day Joshua J Muendle Benedikt B Rosby Brice B Santo Elizabeth E Domingo Antoinette A

PloS one 20180214 2

The purpose of this study was to evaluate whether consumer-level activity trackers can estimate wheelchair strokes and arm ergometer revolutions. Thirty able-bodied participants wore three consumer-level activity trackers (Garmin VivoFit, FitBit Flex, and Jawbone UP24) on the wrist. Participants propelled a wheelchair at fixed frequencies (30, 45 and 60 strokes per minute (spm)) three minutes each and at pre-determined varied frequencies, (30-80 spm) for two minutes. Participants also freely whe ...[more]

PMID: 29444105

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Project description:Hypoactive 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.To 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.Sixteen 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.Division 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.Activ8 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.

Dataset Information

Accuracy and precision of consumer-level activity monitors for stroke detection during wheelchair propulsion and arm ergometry.

Publications

Accuracy and precision of consumer-level activity monitors for stroke detection during wheelchair propulsion and arm ergometry.

Similar Datasets

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