| Literature DB >> 32098628 |
Dennis R Louie1,2, Marie-Louise Bird2,3,4, Carlo Menon5, Janice J Eng6,7.
Abstract
BACKGROUND: Wearable activity monitors that track step count can increase the wearer's physical activity and motivation but are infrequently designed for the slower gait speed and compensatory patterns after stroke. New and available technology may allow for the design of stroke-specific wearable monitoring devices, capable of detecting more than just step counts, which may enhance how rehabilitation is delivered. The objective of this study was to identify important considerations in the development of stroke-specific lower extremity wearable monitoring technology for rehabilitation, from the perspective of physical therapists and individuals with stroke.Entities:
Keywords: Fitness tracker; Remote sensing technology; Stroke; Walking; Wearable electronic devices
Year: 2020 PMID: 32098628 PMCID: PMC7041185 DOI: 10.1186/s12984-020-00666-6
Source DB: PubMed Journal: J Neuroeng Rehabil ISSN: 1743-0003 Impact factor: 4.262
Demographic characteristics of the participants in the five focus groups (physical therapists, individuals with stroke), at the time of inclusion
| Sex, male/female | 1/4 |
| Age, median (range), years | 42 (28–49) |
| Professional experience with stroke, median (range), years | 8 (5.5–18) |
| Sex, male/female | 0/4 |
| Age, median (range), years | 30.5 (28–51) |
| Professional experience with stroke, median (range), years | 5.5 (2–25) |
| Sex, male/female | 0/4 |
| Age, median (range), years | 36 (26–42) |
| Professional experience with stroke, median (range), years | 6.25 (2.5–21) |
| Sex, male/female | 1/3 |
| Age, median (range), years | 29.5 (27–32) |
| Professional experience with stroke, median (range), years | 3.75 (1.5–9) |
| Sex, male/female | 2/1 |
| Age, median (range), years | 55 (47–62) |
| Time since stroke onset, median (range), years | 1.25 (1–3.5) |
| Currently using technology for own health (n) | |
| Yes | 2 |
| No | 1 |
Categories and sub-categories derived from content analysis
| Category | Sub-categories |
|---|---|
| Variability | • Variability of clients • Therapy considerations • Therapy approaches • Focus of therapy |
| Context of use | • Usage location • Usage purpose • Non-representative performance (clinic vs. home) |
| Crucial design features | • Facilitators of adopting technology • Helpful measurements • Ideal design (usability and wearability) • Multimodal/customizable feedback |
| Barriers to adopting technology | • Shortcomings of current technology • Cost a limiting factor • Barriers to integrating technology • Concerns for future technology |
Summary of suggested measures, functions, and design features (usability, wearability) of prospective wearable monitoring technology
| • Muscle activation detection | • Video-pairing |
| • Gait measurements | • Bluetooth connectivity |
| - Timing of muscle activation | • Detects bilaterally |
| - Compensatory pattern detection | • Integrate data with medical records |
| - Heel contact | • Ability to manipulate data |
| - Temporospatial features | • Remote programming and data access |
| - Kinematic features | • Raw and processed data |
| - Toe trajectory | • Comparison to normative data |
| - Stride length | • Continuous feedback/readings |
| • Heart rate monitoring | • Biofeedback |
| • Weight bearing | - Audio (multiple pitches) |
| • Symmetry | - Lights (colour-coded) |
| • Differentiate activation vs. tone | - Vibration |
| • Differentiate concentric vs. eccentric | - On handheld device |
| • Force and loading | - Numeric feedback |
| • Step counts | - Customisable (volume, cues) |
| • Desired variable selection | • Small size, inconspicuous |
| • Reproducible set-up | • Lightweight |
| • Phone interface | • Cosmetically pleasing |
| • Laptop interface | • Simple disinfection |
| • Simple/reusable calibration | • Donning/doffing with one arm |
| • Malfunction alert | • Visual cue at wrist |
| • Turns on upon application | |
| • Usable with one hand | |
| • Customisable app | |
| • Good battery life |