Activity Monitor Placed at the Nonparetic Ankle Is Accurate in Measuring Step Counts During Community Walking in Poststroke Individuals: A Validation Study

Abstract

Background Different environmental factors may affect the accuracy of step‐count activity monitors (AM). However, the validation conditions for AM accuracy largely differ from ecological environments. Objectives To assess and compare the accuracy of AM in counting steps among poststroke individuals: during different locomotor tasks, with AM placed at the nonparetic ankle or hip, and when walking in a laboratory or inside a mall. Design Validation study. Settings Laboratory and community settings. Participants Twenty persons with chronic hemiparesis, independent walkers. Methods First session: participants performed level walking (6‐minute walk test [6MWT]), ramps, and stairs in the laboratory with AM placed at the nonparetic ankle and hip. Second session: participants walked a mall circuit, including the three tasks, with AM placed at the nonparetic ankle. The sessions were video recorded. Main Outcome Measurements Absolute difference between the steps counted by AM and the steps viewed on the video recordings (errors, %); occurrence of errors greater than 10%. Results Median errors were similar for the 6MWT (0.86 [0.22, 7.70]%), ramps (2.17 [0.89, 9.61]%), and stairs (8.33 [2.65, 19.22]%) with AM at the ankle. Step‐count error was lower when AM was placed at the ankle (8.33 [2.65, 19.22]%) than at the hip (9.26 [3.25, 42.63]%, P = .03). The greatest errors were observed among the slowest participants (≤0.4 m/s) on ramps and stairs, whereas some faster participants (>1 m/s) experienced the greatest error during the 6MWT. Median error was slightly increased in the mall circuit (2.67 [0.61, 12.54]%) compared with the 6MWT (0.50 [0.24, 6.79]%, P = .04), with more participants showing errors >10% during the circuit (7 vs 2, P = .05). Conclusions Step counts are accurately measured with AM placed at the nonparetic ankle in laboratory and community settings. Accuracy can be altered by stairs and ramps among the slowest walkers and by prolonged walking tasks among faster walkers. Level of Evidence III.

An investigation into the validity and reliability of mHealth devices for counting steps in chronic stroke survivors

“…The literature reports that the smartphone application placed at the ankle or hip of the non-paretic side during walking did not influence the step count in individuals after chronic stroke during the 6-minute walk test, ramps, or stairs. 28 When the smartphone application was positioned on the non-dominant hand and right pocket, there were no significant differences in step count, regardless of placement, in a study with non-disabled individuals. 21 Thus, the individual should position the device on the most convenient side.…”

Reliability and Validity of Commercially Available Wearable Devices for Measuring Steps, Energy Expenditure, and Heart Rate: Systematic Review

“…A total of 90 studies (979 comparisons) examined wearable device step count measurements compared with reference standard criterion measures of manual counting [ 32 , 34 - 38 , 42 , 46 , 47 , 50 - 53 , 57 , 58 , 72 , 80 - 84 , 88 - 102 , 109 , 114 - 125 , 138 - 141 , 144 - 147 , 149 - 153 , 158 - 161 , 165 , 169 - 171 , 173 ] and accelerometry [ 20 , 60 , 64 - 66 , 85 , 103 , 109 , 126 - 128 , 148 , 154 , 164 ] ( Multimedia Appendix 6 ). Of these, 67 studies recruited healthy adults (mean age 35.4 years, SD 17.4 years), 20 studies recruited adults living with limited mobility/chronic diseases (mean age 60.1 years, SD 10.5 years), two studies recruited children living with limited mobility/chronic diseases (mean age 12.5 years, SD 2.9 years), and one study recruited healthy children (mean age 3.7 years, SD 0.6 years).…”

“…Twelve studies (51 comparisons) with sample sizes ranging from 13 [ 117 , 138 ] to 56 [ 151 ] reported on interdevice reliability for step count [ 50 , 58 , 72 , 85 , 94 , 110 , 113 , 116 , 117 , 121 , 125 , 138 , 151 , 161 , 171 ]. The majority of correlation coefficients for step count interdevice reliability were very strong (n=35), with only a small number (n=3) being reported as strong.…”

Implementation of Wearable Sensing Technology for Movement: Pushing Forward into the Routine Physical Rehabilitation Care Field

“…Using terminology set out in the V3 framework [ 35 ], the problem is not in the verification of the sensor itself, but rather lies in the analytic and clinical validation of the algorithm. People seeking rehabilitation services often do not move normally, such that the algorithms programmed into consumer-grade devices are inaccurate in identifying or quantifying their movement [ 36 , 37 , 38 , 39 , 40 , 41 ]. Continuing with our mainstream metric of walking performance, steps/day has been evaluated across many consumer-grade devices.…”

“…There was wide variability in the accuracy of these devices in individuals with normal gait speed [ 42 , 43 ]. Furthermore, in individuals who utilize assistive devices (e.g., cane, walker) [ 44 , 45 , 46 ], walk with slower speeds (e.g., < 0.8 m/s) [ 36 , 37 , 38 , 39 , 40 , 41 ], or have interruptions in continuous walking [ 47 , 48 ], even higher levels of inaccuracy have been identified. The Fit-Bit Ultra (Fitbit Inc., San Francisco, CA, USA) consumer-level device, for example, has been shown to systematically under-estimate steps for individuals with a diagnosis of stroke and traumatic brain injury over a 2-min walk test, with greater inaccuracy for those who took less steps per minute and those that walked ≤ 0.58 m/s [ 41 ].…”