ArticleSensors (Basel, Switzerland)2019
Development and Validation of Ambulosono: A Wearable Sensor for Bio-Feedback Rehabilitation Training.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 28 citations in OpenAlex.
- Real-time detection and subtyping of "On-meds" freezing of gait in Parkinson's disease using lower-limb acceleration data.Journal of neurology · 2026Observational
- Implementing Gait Kinematic Trajectory Forecasting Models on an Embedded System.Sensors (Basel, Switzerland) · 2024Article
- A wearable device-enabled therapeutic approach to improve joint attention in autism spectrum disorder: a prospective pilot study.Journal of neural transmission (Vienna, Austria : 1996) · 2023Article
- Adaptive cueing strategy for gait modification: A case study using auditory cues.Frontiers in neurorobotics · 2023Article
- Digital health technology combining wearable gait sensors and machine learning improve the accuracy in prediction of frailty.Frontiers in public health · 2023Observational
- A versatile computational algorithm for time-series data analysis and machine-learning models.NPJ Parkinson's disease · 2021Article
- Cueing Paradigms to Improve Gait and Posture in Parkinson's Disease: A Narrative Review.Sensors (Basel, Switzerland) · 2019Review
- Application of Wearable Technology in Clinical Walking and Dual Task Testing.Journal of translational internal medicine · 2019Article
- A novel single-sensor-based method for the detection of gait-cycle breakdown and freezing of gait in Parkinson's disease.Journal of neural transmission (Vienna, Austria : 1996) · 2019Article
- Orchestrating a New Path for Multiple Sclerosis: Achieving Physical, Cognitive, and Emotional Rehabilitation Goals Through Physical and Music Therapy.International journal of MS careArticle
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
Wearable technology-based measurement systems hold potential for the therapeutic and rehabilitation management of patients with various chronic diseases. The purpose of this study was to assess the accuracy and test⁻retest reliability of a new-generation wearable sensor-based system, dubbed Ambulosono, for bio-feedback training. The Ambulosono sensor system was cross-validated by comparing its functionality with the iPod touch (4th generation) sensor system. Fifteen participants underwent a gait test to measure various gait parameters while wearing both the iPod-based and Ambulosono sensors simultaneously. The physically measured values (i.e., the true values) of step length, distance traveled, velocity, and cadence were then compared to those obtained via the two-sensor systems using the same calculation algorithms. While the mean percentage error was <10% for all measured parameters, and the intra-class correlation coefficient revealed a high level of agreement between trials for both sensor systems, it was found that the Ambulosono sensor system outperformed the iPod-based system in some respects. The Ambulosono sensor system possessed both reliability and accuracy in obtaining gait parameter measurements, which suggests it can serve as an economical alternative to the iPod-based system that is currently used in various clinical rehabilitation programs.
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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.