Can wearable real-time biofeedback gait training devices improve gait speed, balance, functional mobility and activities of daily living (ADL) in individuals post-stroke? A systematic review and meta-analysis of randomized controlled trials.

backgroundStroke remains a leading cause of long-term disability, impairing gait, balance, and mobility, which critically reduces independence and increases fall risks. Wearable biofeedback devices have been developed and widely applied for gait rehabilitation, by providing real-time monitoring and adaptive feedback to enhance motor recovery. This systematic review and meta-analysis aimed to synthesize the existing evidence on effects of wearable real-time biofeedback gait training devices on gait parameters and functional abilities in stroke survivors, to guide future clinical practice and research exploration.

methodDatabases of PubMed, EMBASE, MEDLINE, Web of Science, Cochrane Library, CINAHL, PsycInfo, PreQuest, and PEDro were searched up to Sep 13th, 2024. Randomized controlled trials (RCTs) investigating and comparing the effects of wearable real-time biofeedback gait training devices, with general rehabilitative gait training or other controls, in stroke survivors were included. The data including subject/participant characteristics, biofeedback device design/set-up, dosage of interventions, and outcome measures were extracted.

resultA total of 13 RCTs involving 304 participants were included in this systematic review, and 11 RCTs involving 272 participants were included in the meta-analysis. Seven studies measuring gait speed showed statistically significant differences that favored biofeedback gait training over the controls (SMD = 0.41, P = 0.02, n = 204). Subgroup analyses on the efficacy of pressure sensing technology with auditory feedback showed non-significant results, although the P value was close to reaching statistical significance (SMD = 0.30, P = 0.05, n = 166). The pooled data also showed that biofeedback gait training significantly further improved stroke patients’ balance and functional mobility comparing with controls, as evaluated by the Berg Balance Scale (SMD = 0.44, P = 0.03, n = 95) and Timed Up and Go Test (SMD=-0.36, P = 0.01, n = 190), respectively. The meta-analysis showed that biofeedback training was not significantly better than the control treatment in improving activities of daily living, as measured by the Modified Barthel Index (SMD = 0.21, P = 0.38, n = 74).

conclusionsThis review provides moderate quality evidence that wearable real-time biofeedback gait training can improve balance and functional mobility in post-stroke individuals. While a positive overall trend was observed for gait speed, the most prevalent intervention type (pressure sensing with auditory feedback) did not yield a statistically significant effect. No significant benefit was found for activities of daily living. These findings suggest that biofeedback may serve as a useful adjunct to conventional therapy for improving specific aspects of motor function, including balance, functional mobility, and gait speed. Future research should focus on high-quality implementation trials with larger samples, “sham” conditions, and direct comparisons of feedback modalities.