Development and Validation of Ambulosono: A Wearable Sensor for Bio-Feedback Rehabilitation Training

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.

[1]  D. Wrisley,et al.  Reliability, internal consistency, and validity of data obtained with the functional gait assessment. , 2004, Physical therapy.

[2]  Jeffrey M. Hausdorff,et al.  Gait and balance in Parkinson’s disease subtypes: objective measures and classification considerations , 2014, Journal of Neurology.

[3]  Julius Hannink,et al.  Towards Mobile Gait Analysis: Concurrent Validity and Test-Retest Reliability of an Inertial Measurement System for the Assessment of Spatio-Temporal Gait Parameters , 2017, Sensors.

[4]  Asta K. Håberg,et al.  Initial assessment of reliability of a self-administered web-based neuropsychological test battery , 2016, Comput. Hum. Behav..

[5]  Taylor Chomiak,et al.  Gait Differences between Initial Symptom Onset of Tremor-Dominant and Non-Tremor Dominant Sub-Types in Parkinson’s Disease (P1.051) , 2016 .

[6]  John D Sorkin,et al.  The Unified Parkinson's Disease Rating Scale as a predictor of peak aerobic capacity and ambulatory function. , 2012, Journal of rehabilitation research and development.

[7]  A. Fasano,et al.  Technology-based assessment of motor and nonmotor phenomena in Parkinson disease , 2018, Expert review of neurotherapeutics.

[8]  Jianhua Wu,et al.  Biomechanical analysis of the timed up-and-go (TUG) test in children with and without Down syndrome. , 2019, Gait & posture.

[9]  Hamid Khodakarami,et al.  The use of accelerometry as a tool to measure disturbed nocturnal sleep in Parkinson’s disease , 2018, npj Parkinson's Disease.

[10]  Brice Ilharreborde,et al.  Test-retest reliability of an instrumented electronic walkway system (GAITRite) for the measurement of spatio-temporal gait parameters in young patients with Friedreich's ataxia. , 2018, Gait & posture.

[11]  Bin Hu Sustained Relief of Multiple Types of Gait Freezing in Parkinson's Disease: A Novel, Music-Based Meta-Conditioning Treatment Protocol (Ambulosono) (P4.328) , 2016 .

[12]  Conor J Walsh,et al.  Wearable Movement Sensors for Rehabilitation: A Focused Review of Technological and Clinical Advances , 2018, PM & R : the journal of injury, function, and rehabilitation.

[13]  Seong-Gil Kim,et al.  The relationship between anterior pelvic tilt and gait, balance in patient with chronic stroke , 2018, Journal of physical therapy science.

[14]  Chung Chao Liang,et al.  The efficacy of quantitative gait analysis by the GAITRite system in evaluation of parkinsonian bradykinesia. , 2006, Parkinsonism & related disorders.

[15]  Tapas Mondal,et al.  Wearable Sensors for Remote Health Monitoring , 2017, Sensors.

[16]  Renata Noce Kirkwood,et al.  Analysis of symmetry between lower limbs during gait of older women with bilateral knee osteoarthritis , 2018, Aging Clinical and Experimental Research.

[17]  E. Dietrichs,et al.  Viewpoint and practical recommendations from a movement disorder specialist panel on objective measurement in the clinical management of Parkinson’s disease , 2018, npj Parkinson's Disease.

[18]  Nir Giladi,et al.  Characterization of freezing of gait subtypes and the response of each to levodopa in Parkinson's disease , 2003, European journal of neurology.

[19]  Angelo Antonini,et al.  Wearable sensor-based objective assessment of motor symptoms in Parkinson’s disease , 2015, Journal of Neural Transmission.

[20]  Martin J. McKeown,et al.  Differentiating cognitive or motor dimensions associated with the perception of fall-related self-efficacy in Parkinson’s disease , 2018, npj Parkinson's Disease.

[21]  Taylor Chomiak,et al.  A training approach to improve stepping automaticity while dual-tasking in Parkinson's disease , 2017, Medicine.

[22]  Robert Iansek,et al.  The sequence effect and gait festination in Parkinson disease: Contributors to freezing of gait? , 2006, Movement disorders : official journal of the Movement Disorder Society.

[23]  Taylor Chomiak,et al.  A new quantitative method for evaluating freezing of gait and dual-attention task deficits in Parkinson’s disease , 2015, Journal of Neural Transmission.

[24]  Junaidah Bte Mustafa Kamal.,et al.  Remote health monitoring. , 2013 .

[25]  W. Byblow,et al.  Stride length regulation in Parkinson's disease: the use of extrinsic, visual cues. , 2000, Brain : a journal of neurology.