Step Monitor Accuracy During PostStroke Physical Therapy and Simulated Activities

A Large Harmonized Upper and Lower Limb Accelerometry Dataset: A Resource for Rehabilitation Scientists

Wearable sensors can measure movement in daily life, an outcome that is salient to patients, and have been critical to accelerating progress in rehabilitation research and practice. However, collecting and processing sensor data is burdensome, leaving many scientists with limited access to such data. To address these challenges, we present a harmonized, wearable sensor dataset that combines 2,885 recording days of sensor data from the upper and lower limbs from eight studies. The dataset includes 790 individuals ages 0 - 90, nearly equal sex proportions (53% male, 47% female), and representation from a range of demographic backgrounds (69.4% White, 24.9% Black, 1.8% Asian) and clinical conditions (46% neurotypical, 31% stroke, 7% Parkinson's disease, 6% orthopedic conditions, and others). The dataset is publicly available and accompanied by open source code and an app that allows for interaction with the data. This dataset will facilitate the use of sensor data to advance rehabilitation research and practice, improve the reproducibility and replicability of wearable sensor studies, and minimize costs and duplicated scientific efforts.

Speed- and Endurance-Based Classifications of Community Ambulation Post-Stroke Revisited: The Importance of Location in Walking Performance Measurement

BACKGROUND

Gait speed or 6-minute walk test are frequently used to project community ambulation abilities post-stroke by categorizing individuals as household ambulators, limited, or unlimited community ambulators. However, whether improved clinically-assessed gait outcomes truly translate into enhanced real-world community ambulation remains uncertain.

OBJECTIVE

This cross-sectional study aimed to examine differences in home and community ambulation between established categories of speed- and endurance-based classification systems of community ambulation post-stroke and compare these with healthy controls.

METHODS

Sixty stroke survivors and 18 healthy controls participated. Stroke survivors were categorized into low-speed, medium-speed, or high-speed groups based on speed-based classifications and into low-endurance, medium-endurance, or high-endurance groups based on the endurance-based classification. Home and community steps/day were quantified using Global Positioning System and accelerometer devices over 7 days.

RESULTS

The low-speed groups exhibited fewer home and community steps/day than their medium- and high-speed counterparts (P < .05). The low-endurance group took fewer community steps/day than the high-endurance group (P < .05). Despite vast differences in clinical measures of gait speed and endurance, the medium-speed/endurance groups did not differ in their home and community steps/day from the high-speed/endurance groups, respectively. Stroke survivors took 48% fewer home steps/day and 77% fewer community steps/day than healthy controls.

CONCLUSIONS

Clinical classification systems may only distinguish home ambulators from community ambulators, but not between levels of community ambulation, especially beyond certain thresholds of gait speed and endurance. Clinicians should use caution when predicting community ambulation status through clinical measures, due to the limited translation of these classification systems into the real world.

Agreement of activity monitors for assessment of patients with sub-acute stroke in an inpatient rehabilitation facility

PURPOSE

Determine the level of agreement of three activity monitors compared with the gold standard (video review) on the activity level of patients with stroke.

METHODS

A prospective, observational, agreement study was performed on 47 individuals with sub-acute stroke in an inpatient rehabilitation facility. Data was collected during one physical therapy session. Individuals wore three device types; Actigraph (AG), Activpal (AP), and stepwatch activity monitor (SAM). Variables assessed were step counts for each limb (hemiparetic and non-hemiparetic) and percent time standing and other.

ANALYSIS

Results from the activity monitors were compared to the video review and assessed for agreement using the intraclass correlation coefficient (ICC) and accuracy of mean difference from video observation.

RESULTS

The step counts with the SAM on the non-hemiparetic limb had the highest ICC for step counts (ICC = 0.98, p < 0.001) and were overestimated with 21% accuracy. The SAM on the hemiparetic limb had 9.7% accuracy (ICC = 0.92, p < 0.001). For percent standing time all devices overestimated with poor reliability. For percent other activity time, the AP had the best accuracy and underestimated for both the hemiparetic limb (9.9% accuracy; ICC = 0.90, p < 0.001) and non-hemiparetic limb (8.3% accuracy; ICC = 0.84, p < 0.001).

CONCLUSIONS

The use of multiple devices may be warranted to capture an accurate understanding of activity levels in this population of individuals with sub-acute stroke. There are concerns with all monitors and clinicians and researchers should be aware of what measures they are wanting to understand about their population.

Measurement properties of device-based physical activity instruments in ambulatory adults with physical disabilities and/or chronic diseases: a scoping review

BACKGROUND

People with physical disabilities and/or chronic diseases tend to have an inactive lifestyle. Monitoring physical activity levels is important to provide insight on how much and what types of activities people with physical disabilities and/or chronic diseases engage in. This information can be used as input for interventions to promote a physically active lifestyle. Therefore, valid and reliable physical activity measurement instruments are needed. This scoping review aims 1) to provide a critical mapping of the existing literature and 2) directions for future research on measurement properties of device-based instruments assessing physical activity behavior in ambulant adults with physical disabilities and/or chronic diseases.

METHODS

Four databases (MEDLINE, CINAHL, Web of Science, Embase) were systematically searched from 2015 to April 16th 2023 for articles investigating measurement properties of device-based instruments assessing physical activity in ambulatory adults with physical disabilities and/or chronic diseases. For the majority, screening and selection of eligible studies were done in duplicate. Extracted data were publication data, study data, study population, device, studied measurement properties and study outcome. Data were synthesized per device.

RESULTS

One hundred three of 21566 Studies were included. 55 Consumer-grade and 23 research-grade devices were studied on measurement properties, using 14 different physical activity outcomes, in 23 different physical disabilities and/or chronic diseases. ActiGraph (n = 28) and Fitbit (n = 39) devices were most frequently studied. Steps (n = 68) was the most common used physical activity outcome. 97 studies determined validity, 11 studies reliability and 6 studies responsiveness.

CONCLUSION

This scoping review shows a large variability in research on measurement properties of device-based instruments in ambulatory adults with physical disabilities and/or chronic diseases. The variability highlights a need for standardization of and consensus on research in this field. The review provides directions for future research.