Using Accelerometer and Gyroscopic Measures to Quantify Postural Stability

Abstract

Context: Force platforms and 3-dimensional motion-capture systems provide an accurate method of quantifying postural stability. Substantial cost, space, time to administer, and need for trained personnel limit widespread use of biomechanical techniques in the assessment of postural stability in clinical or field environments.Objective: To determine whether accelerometer and gyroscope data sampled from a consumer electronics device (iPad2) provide sufficient resolution of center-of-gravity (COG) movements to accurately quantify postural stability in healthy young people.Design: Controlled laboratory study. Setting: Research laboratory in an academic medical center.Patients or Other Participants: A total of 49 healthy individuals (age ¼ 19.5 6 3.1 years, height ¼ 167.7 6 13.2 cm, mass ¼ 68.5 6 17.5 kg).Intervention(s): Participants completed the NeuroCom Sensory Organization Test (SOT) with an iPad2 affixed at the sacral level.Main Outcome Measure(s): Primary outcomes were equilibrium scores from both systems and the time series of the angular displacement of the anteroposterior COG sway during each trial. A Bland-Altman assessment for agreement was used to compare equilibrium scores produced by the NeuroCom and iPad2 devices. Limits of agreement was defined as the mean bias (NeuroCom À iPad) 6 2 standard deviations. Mean absolute percentage error and median difference between the NeuroCom and iPad2 measurements were used to evaluate how closely the real-time COG sway measured by the 2 systems tracked each other.Results: The limits between the 2 devices ranged from À0.58 to 0.58 in SOT condition 1 to À2.98 to 1.38 in SOT condition 5. The largest absolute value of the measurement error within the 95% confidence intervals for all conditions was 2.98. The mean absolute percentage error analysis indicated that the iPad2 tracked NeuroCom COG with an average error ranging from 5.87% to 10.42% of the NeuroCom measurement across SOT conditions.Conclusions: The iPad2 hardware provided data of sufficient precision and accuracy to quantify postural stability. Accuracy, portability, and affordability make using the iPad2 a reasonable approach for assessing postural stability in clinical and field environments.Key Words: concussions, motor function, motor control, biomechanics Key PointsThe accelerometer and gyroscope within the iPad2 provided data of sufficient quantity and quality to enable accurate evaluation of postural stability. The accuracy, portability, availability, and affordability of mobile devices can enable health care providers in various clinical and field settings to evaluate postural stability in athletes. To improve clinical outcomes, mobile devices can be a mechanism by which sophisticated biomechanical algorithms are translated to the broader field of athletic trainers and clinical teams treating patients with concussions. The accuracy and reliability of mobile devices must be validated before these systems are used to assess cognitive or motor function.

Inertial Sensor Technology Can Capture Changes in Dynamic Balance Control during the Y Balance Test

“…Secondly, no motion capture or force platform system was incorporated into this study. However, 95EV, derived from a lumbar-mounted accelerometer and gyroscope has previously been compared to force platform and 3D motion capture systems [20]. Alberts et al [20] demonstrated that during components of the balance error scoring system, the kinematic data obtained from an iPad embedded inertial sensor are of sufficient quality relative to motion capture data to accurately quantify static balance.…”

“…However, 95EV, derived from a lumbar-mounted accelerometer and gyroscope has previously been compared to force platform and 3D motion capture systems [20]. Alberts et al [20] demonstrated that during components of the balance error scoring system, the kinematic data obtained from an iPad embedded inertial sensor are of sufficient quality relative to motion capture data to accurately quantify static balance. Additionally, the repeated pre-fatigue baseline testing points demonstrated the relatively low levels of within-subject variability across the 3 time points, indicating its relative stability.…”

“…3) [14, 20]. This measure was used previously to measure postural control during the Balance Error Scoring System and shown to have a high correlation with motion capture-derived sway measures [21].…”

“…Such systems have overcome many of the key limitations of traditional biomechanical systems (such as force platforms and marker-based motion capture), allowing for the unobtrusive quantification of traditional clinical assessments, such as the Timed Up and Go Test [19] and the Balance Error Scoring System [14, 20]. These novel digital biomarkers are capable of capturing subtle alterations in motor function that are present in individuals at an increased risk of falls [19] and following concussive head injuries [14].…”

Objective Classification of Dynamic Balance Using a Single Wearable Sensor

“…Such systems address some of the aforementioned limitations of traditional motion capture, as they allow for inexpensive, accessible quantification of human movement, in an unconstrained environment (Giggins et al, 2013). These IMU systems have been used in the objective quantification of a range of activities, from static balance tasks (King et al, 2014, Alberts et al, 2015, Furman et al, 2013, to dynamic tasks such as the squat and single leg squat , walking (Zijlstra andHof, 2003, Yang et al, 2013) and running (Lee et al, 2010). Early work investigating the use of IMUs in balance assessment has shown that a static balance assessment, instrumented with an IMU mounted on the lumbar spine, was not as effective as the traditional subjectively scored assessment in identifying balance deficits post-concussion (Furman et al, 2013).…”