ArticlePilot and feasibility studies2024
Real-time auditory feedback for improving gait and walking in people with Parkinson's disease: a pilot and feasibility trial.
Article in Pilot and feasibility studies, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Effects of Wearable Devices on Parkinson Disease: Systematic Review and Meta-Analysis of Randomized Controlled Trials Within the International Classification of Functioning, Disability, and Health Framework.Journal of medical Internet research · 2026Pooled it
- Effects of wearable devices on gait, balance, and motor function in people with Parkinson's disease: a systematic review and meta-analysis.Frontiers in public health · 2026Pooled it
- Feasibility of IMU-Based Wearable Sonification: Toward Personalized, Real-Time Gait Monitoring and Rehabilitation.Biosensors · 2025Article
- Comparability of Methods for Remotely Assessing Gait Quality.Sensors (Basel, Switzerland) · 2025Article
- Foundations and Strategic Vision of the Canadian Translational Geroscience Network.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025Article
- Evidence for the Link Between Non-Motor Symptoms, Kinematic Gait Parameters, and Physical Function in People with Parkinson's Disease.Bioengineering (Basel, Switzerland) · 2025Article
- A review of concurrent sonified biofeedback in balance and gait training.Journal of neuroengineering and rehabilitation · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
backgroundTechnology is poised to bridge the gap between demand for therapies to improve gait in people with Parkinson's and available resources. A wearable sensor, Heel2Toe™, a small device that attaches to the side of the shoe and gives a sound each time the person starts their step with a strong heel strike, has been developed and pre-tested by a team at McGill University. The objective of this study was to estimate feasibility and efficacy potential of the Heel2Toe™ sensor in changing walking capacity and gait pattern in people with Parkinson's.
methodsA pilot study was carried out involving 27 people with Parkinson's randomized 2:1 to train with the Heel2Toe[TM] sensor and or to train with recommendations from a gait-related workbook.
resultsA total of 21 completed the 3-month evaluation, 14 trained with the Heel2Toe[TM] sensor, and 7 trained with the workbook. Thirteen of 14 people in the Heel2Toe group improved over measurement error on the primary outcome, the 6-Minute Walk Test, (mean change 66.4 m) and 0 of the 7 in the Workbook group (mean change - 19.4 m): 4 of 14 in the Heel2Toe group made reliable change and 0 of 7 in the Workbook group. Improvements in walking distance were accompanied by improvements in gait quality. Forty percent of participants in the intervention group were strongly satisfied with their technology experience and an additional 37% were satisfied.
conclusionsDespite some technological difficulties, feasibility and efficacy potential of the Heel2Toe sensor in improving gait in people with Parkinson's was supported.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.