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 mobile phone application, which 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 8 different balance exercises separately for the right and left legs. Accelerometer readings were obtained from each mobile phone 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 2-way interaction was revealed between exercise condition and the body position of the phone (P<.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 app has utility as a measurement tool for standing balance.

[1]  K. Słomka,et al.  Evaluation of the Limits of Stability (LOS) Balance Test , 2008 .

[2]  D. Padua,et al.  Evidence Supporting Balance Training in Healthy Individuals: A Systemic Review , 2009, Journal of strength and conditioning research.

[3]  Jay Smith,et al.  Intrarater and Interrater Reliability of the Balance Error Scoring System (BESS) , 2009, PM & R : the journal of injury, function, and rehabilitation.

[4]  Paul McCrory,et al.  Validity and reliability of the Nintendo Wii Balance Board for assessment of standing balance. , 2010, Gait & posture.

[5]  Noel E. O'Connor,et al.  Classification of Sporting Activities Using Smartphone Accelerometers , 2013, Sensors.

[6]  Merryn J Mathie,et al.  Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement , 2004, Physiological measurement.

[7]  Gerard Boyle,et al.  Correlation of accelerometry with clinical balance tests in older fallers and non-fallers. , 2008, Age and ageing.

[8]  Hassan Ghasemzadeh,et al.  Body sensor networks to evaluate standing balance: interpreting muscular activities based on inertial sensors , 2008, HealthNet '08.

[9]  Garrett Mehl,et al.  H_pe for mHealth: More "y" or "o" on the horizon? , 2013, Int. J. Medical Informatics.

[10]  Antonio I Cuesta-Vargas,et al.  Differences in Trunk Accelerometry Between Frail and Nonfrail Elderly Persons in Sit-to-Stand and Stand-to-Sit Transitions Based on a Mobile Inertial Sensor , 2013, JMIR mHealth and uHealth.

[11]  Bruce Walker,et al.  The test-retest reliability of centre of pressure measures in bipedal static task conditions--a systematic review of the literature. , 2010, Gait & posture.

[12]  I. bonan,et al.  Clinical tools for assessing balance disorders , 2008, Neurophysiologie Clinique/Clinical Neurophysiology.

[13]  J. Donovan,et al.  Why don't patients do their exercises? Understanding non-compliance with physiotherapy in patients with osteoarthritis of the knee , 2001, Journal of epidemiology and community health.

[14]  A. Monteiro Mobile health , 2014, Radiologia brasileira.

[15]  B. Rowe,et al.  Effectiveness of a home-based balance-training program in reducing sports-related injuries among healthy adolescents: a cluster randomized controlled trial , 2005, Canadian Medical Association Journal.

[16]  F. Horak Clinical measurement of postural control in adults. , 1987, Physical therapy.

[17]  C. Emery,et al.  Is there a clinical standing balance measurement appropriate for use in sports medicine? A review of the literature. , 2003, Journal of science and medicine in sport.

[18]  Sara Kiesler,et al.  iPod for Home Balance Rehabilitation Exercise Monitoring , 2012, 2012 16th International Symposium on Wearable Computers.

[19]  Lorenzo Chiari,et al.  ISway: a sensitive, valid and reliable measure of postural control , 2012, Journal of NeuroEngineering and Rehabilitation.

[20]  David R. Bell,et al.  Systematic Review of the Balance Error Scoring System , 2011, Sports health.

[21]  R. Moe-Nilssen,et al.  Trunk accelerometry as a measure of balance control during quiet standing. , 2002, Gait & posture.

[22]  Audie A Atienza,et al.  Mobile health technology evaluation: the mHealth evidence workshop. , 2013, American journal of preventive medicine.

[23]  D. Petitti,et al.  A Mobile Cloud-Based Parkinson’s Disease Assessment System for Home-Based Monitoring , 2015, JMIR mHealth and uHealth.

[24]  J. P. Paul,et al.  What is balance? , 2000, Clinical rehabilitation.

[25]  P. Papagelopoulos,et al.  Accelerometry for Evaluation of Gait Pattern in Healthy Soccer Athletes , 2009, The Journal of international medical research.

[26]  A. Rodríguez-Molinero,et al.  Validation of a Portable Device for Mapping Motor and Gait Disturbances in Parkinson’s Disease , 2015, JMIR mHealth and uHealth.

[27]  Steven Truijen,et al.  Clinical assessment of balance: Normative data, and gender and age effects , 2008, International journal of audiology.

[28]  Lorenzo Chiari,et al.  Validity of a Smartphone-based instrumented Timed Up and Go. , 2012, Gait & posture.

[29]  L. Swartz,et al.  Scaling Up mHealth: Where Is the Evidence? , 2013, PLoS medicine.