A Game Changer: 'The Use of Digital Technologies in the Management of Upper Limb Rehabilitation'

Requirements for home-based upper extremity rehabilitation using wearable motion sensors for stroke patients: a user-centred approach

PURPOSE

Telerehabilitation systems have the potential to enable therapists to monitor and assist stroke patients in achieving high-intensity upper extremity exercise in the home environment. We adopted an iterative user-centred approach, including multiple data sources and meetings with end-users and stakeholders to define the user requirements for home-based upper extremity rehabilitation using wearable motion sensors for subacute stroke patients.

METHODS

We performed a requirement analysis consisting of the following steps: 1) context & groundwork; 2) eliciting requirements; 3) modelling & analysis; 4) agreeing requirements. During these steps, a pragmatic literature search, interviews and focus groups with stroke patients, physiotherapists and occupational therapists were performed. The results were systematically analysed and prioritised into "must-haves", "should-haves", and "could-haves".

RESULTS

We formulated 33 functional requirements: eighteen must-have requirements related to blended care (2), exercise principles (7), exercise delivery (3), exercise evaluation (4), and usability (2); ten should-haves; and five could-haves. Six movement components, including twelve exercises and five combination exercises, are required. For each exercise, appropriate exercise measures were defined.

CONCLUSION

This study provides an overview of functional requirements, required exercises, and required exercise measures for home-based upper extremity rehabilitation using wearable motion sensors for stroke patients, which can be used to develop home-based upper extremity rehabilitation interventions. Moreover, the comprehensive and systematic requirement analysis used in this study can be applied by other researchers and developers when extracting requirements for designing a system or intervention in a medical context.

Examining Usability, Acceptability, and Adoption of a Self-Directed, Technology-Based Intervention for Upper Limb Rehabilitation After Stroke: Cohort Study

BACKGROUND

Upper limb (UL) recovery after stroke is strongly dependent upon rehabilitation dose. Rehabilitation technologies present pragmatic solutions to dose enhancement, complementing therapeutic activity within conventional rehabilitation, connecting clinicians with patients remotely, and empowering patients to drive their own recovery. To date, rehabilitation technologies have been poorly adopted. Understanding the barriers to adoption may shape strategies to enhance technology use and therefore increase rehabilitation dose, thus optimizing recovery potential.

OBJECTIVE

We examined the usability, acceptability, and adoption of a self-directed, exercise-gaming technology within a heterogeneous stroke survivor cohort and investigated how stroke survivor characteristics, technology usability, and attitudes toward technology influenced adoption.

METHODS

A feasibility study of a novel exercise-gaming technology for self-directed UL rehabilitation in early subacute stroke survivors (N=30) was conducted in an inpatient, acute hospital setting. Demographic and clinical characteristics were recorded; participants' performance in using the system (usability) was assessed using a 4-point performance rating scale (adapted from the Barthel index), and adherence with the system was electronically logged throughout the trial. The technology acceptance model was used to formulate a survey examining the acceptability of the system. Spearman rank correlations were used to examine associations between participant characteristics, user performance (usability), end-point technology acceptance, and intervention adherence (adoption).

RESULTS

The technology was usable for 87% (n=26) of participants, and the overall technology acceptance rating was 68% (95% CI 56%-79%). Participants trained with the device for a median of 26 (IQR 16-31) minutes daily over an enrollment period of 8 (IQR 5-14) days. Technology adoption positively correlated with user performance (usability) (ρ=0.55; 95% CI 0.23-0.75; P=.007) and acceptability as well as domains of perceived usefulness (ρ=0.42; 95% CI 0.09-0.68; P=.03) and perceived ease of use (ρ=0.46; 95% CI 0.10-0.74; P=.02). Technology acceptance decreased with increased global stroke severity (ρ=-0.56; 95% CI -0.79 to -0.22; P=.007).

CONCLUSIONS

This technology was usable and acceptable for the majority of the cohort, who achieved an intervention dose with technology-facilitated, self-directed UL training that exceeded conventional care norms. Technology usability and acceptability were determinants of adoption and appear to be mediated by stroke severity. The results demonstrate the importance of selecting technologies for stroke survivors on the basis of individual needs and abilities, as well as optimizing the accessibility of technologies for the target user group. Facilitating changes in stroke survivors' beliefs and attitudes toward rehabilitation technologies may enhance adoption. Further work is needed to understand how technology can be optimized to benefit those with more severe stroke.

Can Individuals Poststroke Improve Their Performance in Reaction and Movement Times in a Nonimmersive Serious Game with Practice? A Cross-Sectional Study

Objective: To verify if individuals' poststroke and healthy controls would improve their performance in reaction and movement times practicing a serious game task using the upper limb movements. Materials and Methods: We evaluated 30 individuals poststroke and 30 healthy controls, matched for age and sex. We used the "Association Game for Rehabilitation" (AGaR) where participants played by matching a pair of images whose meanings were similar. Hand movements were captured by a Kinect system and poststroke participants used their nonparetic upper limb. Reaction time and movement times (time to select an image and movement time to the target) were measured. Data were analyzed using multiple analysis of variance. Results: Performance improved for both groups across all variables with better performance in movement times than reaction time only for poststroke individuals. Conclusions: Upper limb movements using nonimmersive serious games enhanced motor performance in reaction and movement times for healthy controls and individuals poststroke. ReBEC Trial Registration: RBR-4m4pk; Registeted on 08/24/2018.

Leap Motion Controller Video Game-Based Therapy for Upper Extremity Motor Recovery in Patients with Central Nervous System Diseases. A Systematic Review with Meta-Analysis

Leap Motion Controller (LMC) is a virtual reality device that can be used in the rehabilitation of central nervous system disease (CNSD) motor impairments. This review aimed to evaluate the effect of video game-based therapy with LMC on the recovery of upper extremity (UE) motor function in patients with CNSD. A systematic review with meta-analysis was performed in PubMed Medline, Web of Science, Scopus, CINAHL, and PEDro. We included five randomized controlled trials (RCTs) of patients with CNSD in which LMC was used as experimental therapy compared to conventional therapy (CT) to restore UE motor function. Pooled effects were estimated with Cohen's standardized mean difference (SMD) and its 95% confidence interval (95% CI). At first, in patients with stroke, LMC showed low-quality evidence of a large effect on UE mobility (SMD = 0.96; 95% CI = 0.47, 1.45). In combination with CT, LMC showed very low-quality evidence of a large effect on UE mobility (SMD = 1.34; 95% CI = 0.49, 2.19) and the UE mobility-oriented task (SMD = 1.26; 95% CI = 0.42, 2.10). Second, in patients with non-acute CNSD (cerebral palsy, multiple sclerosis, and Parkinson's disease), LMC showed low-quality evidence of a medium effect on grip strength (GS) (SMD = 0.47; 95% CI = 0.03, 0.90) and on gross motor dexterity (GMD) (SMD = 0.73; 95% CI = 0.28, 1.17) in the most affected UE. In combination with CT, LMC showed very low-quality evidence of a high effect in the most affected UE on GMD (SMD = 0.80; 95% CI = 0.06, 1.15) and fine motor dexterity (FMD) (SMD = 0.82; 95% CI = 0.07, 1.57). In stroke, LMC improved UE mobility and UE mobility-oriented tasks, and in non-acute CNSD, LMC improved the GS and GMD of the most affected UE and FMD when it was used with CT.