JMIR Rehabilitation and Assistive Technologies

Novel use of a smartphone to measure standing balance

Background: Balance assessment and training is utilized by clinicians and their patients to measure and improve balance. There is, however, little consistency in terms of how clinicians, researchers, and patients measure standing balance. Utilizing the inherent sensors in every smartphone a mobile application was developed to provide a method of objectively measuring standing balance. Objective: We aimed to determine if a smartphone application, that utilizes the phone’s accelerometer, can quantify standing balance. Methods: Three smartphones were positioned simultaneously above the participants’ malleolus and patella and at the level of the umbilicus. Once secured, the myAnkle application was initiated to measure acceleration. Forty-eight participants completed eight different balance exercises separately for the right and left legs. Accelerometer readings were obtained from each smartphone and mean acceleration was calculated for each exercise at each ankle and knee and the torso. Results: Mean acceleration vector magnitude was reciprocally transformed to address skewness in the data distribution. Repeated measures ANOVAs were completed using the transformed data. A significant two-way interaction was revealed between exercise condition and the body position of the phone (p<0.001). Post-hoc tests indicated higher acceleration vector magnitude for exercises of greater difficulty. ANOVAs at each body position were conducted to examine the effect of exercise. The results revealed the knee as the location most sensitive for the detection of differences in acceleration between exercises. The accelerometer ranking of exercise difficulty showed high agreement with expert clinical rater rankings (kappa statistic>0.9). Conclusions: The myAnkle application revealed significantly greater acceleration magnitude for exercises of greater difficulty. Positioning of the mobile phone at the knee proved to be the most sensitive to changes in accelerometer values due to exercise difficulty. Application validity was shown through comparison with clinical raters. As such, the myAnkle smartphone application has utility as a measurement tool for standing balance. Clinical Trial: N/A

2014-10-27

Open Access and no publication or submission fees!

JMIR Rehabilitation and Assistive Technologies is a new spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2010: 4.7). JMIR Rehab focusses on development and evaluation of rehabilitation and cyborg technologies, i.e. assistive, adaptive, and rehabilitative hi-tech approaches, for example robotic/medical devices, prosthetics, and software for people with chronic or acute conditions and disabilities, as well as for performance enhancement of healthy individuals.

Become a founding author and/or editor in this emerging field and submit your paper to JMIR Rehab and/or apply as section editor (you must have published and reviewed for JMIR to be eligible as editorial board member).

Published by JMIR Publications, publisher of the Journal of Medical Internet Research (JMIR), the leading eHealth/mHealth journal (Impact Factor 2013: 4.4), JMIR Mental Health publishes even faster and has a broader scope with including papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research.  JMIR Rehabilitation journal features a rapid and thorough peer-review process, professional copyediting, professional production of PDF, XHTML, and XML proofs (ready for deposit in PubMed Central/PubMed), and an ipad App (in prep.). JMIR Rehab adheres to the same quality standards as JMIR and all articles published here are also cross-listed in the Table of Contents of JMIR, the worlds' leading medical journal in health sciences / health services research and health informatics (http://www.jmir.org/issue/current).

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  • (cc) Lam et al. CC-BY-SA-2.0, please cite as (http://rehab.jmir.org/article/viewFile/3484/1/52473).

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    Background: Neurorehabilitation therapies exploiting the use-dependent plasticity of our neuromuscular system are devised to help patients who suffer from injuries or diseases of this system. These therapies take advantage of the fact that the motor activity alters the properties of our neurons and muscles, including the pattern of their connectivity, and thus their functionality. Hence, a sensor-motor treatment where patients makes certain movements will help them (re)learn how to move the affected body parts. But these traditional rehabilitation processes are usually repetitive and lengthy, reducing motivation and adherence to the treatment, and thus limiting the benefits for the patients. Objective: Our goal was to create innovative neurorehabilitation therapies based on THERAPIST, a socially assistive robot. THERAPIST is an autonomous robot that is able to find and execute plans and adapt them to new situations in real-time. The software architecture of THERAPIST monitors and determines the course of action, learns from previous experiences, and interacts with people using verbal and non-verbal channels. THERAPIST can increase the adherence of the patient to the sessions using serious games. Data are recorded and can be used to tailor patient sessions. Methods: We hypothesized that pediatric patients would engage better in a therapeutic non-physical interaction with a robot, facilitating the design of new therapies to improve patient motivation. We propose RoboCog, a novel cognitive architecture. This architecture will enhance the effectiveness and time-of-response of complex multi-degree-of-freedom robots designed to collaborate with humans, combining two core elements: a deep and hybrid representation of the current state, own, and observed; and a set of task-dependent planners, working at different levels of abstraction but connected to this central representation through a common interface. Using RoboCog, THERAPIST engages the human partner in an active interactive process. But RoboCog also endows the robot with abilities for high-level planning, monitoring, and learning. Thus, THERAPIST engages the patient through different games or activities, and adapts the session to each individual. Results: RoboCog successfully integrates a deliberative planner with a set of modules working at situational or sensorimotor levels. This architecture also allows THERAPIST to deliver responses at a human rate. The synchronization of the multiple interaction modalities results from a unique scene representation or model. THERAPIST is now a socially interactive robot that, instead of reproducing the phrases or gestures that the developers decide, maintains a dialogue and autonomously generate gestures or expressions. THERAPIST is able to play simple games with human partners, which requires humans to perform certain movements, and also to capture the human motion, for later analysis by clinic specialists. Conclusions: The initial hypothesis was validated by our experimental studies showing that interaction with the robot results in highly attentive and collaborative attitudes in pediatric patients. We also verified that RoboCog allows the robot to interact with patients at human rates. However, there remain many issues to overcome. The development of novel hands-off rehabilitation therapies will require the intersection of multiple challenging directions of research that we are currently exploring.

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  • Novel use of a smartphone to measure standing balance

    Date Submitted: Apr 8, 2015

    Open Peer Review Period: Apr 26, 2015 - Jun 21, 2015

    Background: Balance assessment and training is utilized by clinicians and their patients to measure and improve balance. There is, however, little consistency in terms of how clinicians, researchers,...

    Background: Balance assessment and training is utilized by clinicians and their patients to measure and improve balance. There is, however, little consistency in terms of how clinicians, researchers, and patients measure standing balance. Utilizing the inherent sensors in every smartphone a mobile application was developed to provide a method of objectively measuring standing balance. Objective: We aimed to determine if a smartphone application, that utilizes the phone’s accelerometer, can quantify standing balance. Methods: Three smartphones were positioned simultaneously above the participants’ malleolus and patella and at the level of the umbilicus. Once secured, the myAnkle application was initiated to measure acceleration. Forty-eight participants completed eight different balance exercises separately for the right and left legs. Accelerometer readings were obtained from each smartphone and mean acceleration was calculated for each exercise at each ankle and knee and the torso. Results: Mean acceleration vector magnitude was reciprocally transformed to address skewness in the data distribution. Repeated measures ANOVAs were completed using the transformed data. A significant two-way interaction was revealed between exercise condition and the body position of the phone (p<0.001). Post-hoc tests indicated higher acceleration vector magnitude for exercises of greater difficulty. ANOVAs at each body position were conducted to examine the effect of exercise. The results revealed the knee as the location most sensitive for the detection of differences in acceleration between exercises. The accelerometer ranking of exercise difficulty showed high agreement with expert clinical rater rankings (kappa statistic>0.9). Conclusions: The myAnkle application revealed significantly greater acceleration magnitude for exercises of greater difficulty. Positioning of the mobile phone at the knee proved to be the most sensitive to changes in accelerometer values due to exercise difficulty. Application validity was shown through comparison with clinical raters. As such, the myAnkle smartphone application has utility as a measurement tool for standing balance. Clinical Trial: N/A