Predicted Threshold for Seated Stability: Estimation of Margin of Stability Using Wearable Inertial Sensors

Motion Tracking of Daily Living and Physical Activities in Health Care: Systematic Review From Designers' Perspective

BACKGROUND

Motion tracking technologies serve as crucial links between physical activities and health care insights, facilitating data acquisition essential for analyzing and intervening in physical activity. Yet, systematic methodologies for evaluating motion tracking data, especially concerning user activity recognition in health care applications, remain underreported.

OBJECTIVE

This study aims to systematically review motion tracking in daily living and physical activities, emphasizing the critical interaction among devices, users, and environments from a design perspective, and to analyze the process involved in health care application research. It intends to delineate the design and application intricacies in health care contexts, focusing on enhancing motion tracking data's accuracy and applicability for health monitoring and intervention strategies.

METHODS

Using a systematic review, this research scrutinized motion tracking data and their application in health care and wellness, examining studies from Scopus, Web of Science, EBSCO, and PubMed databases. The review used actor network theory and data-enabled design to understand the complex interplay between humans, devices, and environments within these applications.

RESULTS

Out of 1501 initially identified studies, 54 (3.66%) were included for in-depth analysis. These articles predominantly used accelerometer and gyroscope sensors (n=43, 80%) to monitor and analyze motion, demonstrating a strong preference for these technologies in capturing both dynamic and static activities. While incorporating portable devices (n=11, 20%) and multisensor configurations (n=16, 30%), the application of sensors across the body (n=15, 28%) and within physical spaces (n=17, 31%) highlights the diverse applications of motion tracking technologies in health care research. This diversity reflects the application's alignment with activity types ranging from daily movements to specialized scenarios. The results also reveal a diverse participant pool, including the general public, athletes, and specialized groups, with a focus on healthy individuals (n=31, 57%) and athletes (n=14, 26%). Despite this extensive application range, the focus primarily on laboratory-based studies (n=39, 72%) aimed at professional uses, such as precise activity identification and joint functionality assessment, emphasizes a significant challenge in translating findings from controlled environments to the dynamic conditions of everyday physical activities.

CONCLUSIONS

This study's comprehensive investigation of motion tracking technology in health care research reveals a significant gap between the methods used for data collection and their practical application in real-world scenarios. It proposes an innovative approach that includes designers in the research process, emphasizing the importance of incorporating data-enabled design framework. This ensures that motion data collection is aligned with the dynamic and varied nature of daily living and physical activities. Such integration is crucial for developing health applications that are accessible, intuitive, and tailored to meet diverse user needs. By leveraging a multidisciplinary approach that combines design, engineering, and health sciences, the research opens new pathways for enhancing the usability and effectiveness of health technologies.

Functional balance assessment for predicting future recurrent falls in non-ambulatory individuals with spinal cord injury: a prospective pilot study

BACKGROUND

Functional assessments easy to administer within the clinic to identify non-ambulatory individuals with spinal cord injury at risk of recurrent falls are needed.

PURPOSE

To examine the ability of functional balance and transfer quality to predict recurrent falls.

METHODS

This 6-month prospective study examined remote assessments of transfer quality using the Transfer Assessment Instrument and functional sitting balance with the Function in Sitting Test and the Trunk Control Test. Then, participants prospectively monitored their falls for 6-month using fall diaries. Frequency of falls was categorized as infrequent fallers (≤2 falls) and recurrent fallers (>2 falls). A multivariable logistic regression analysis was conducted. A Receiver Operating Characteristic curve was performed to determine the area under the curve, the sensitivity, and the specificity of the model.

RESULTS

Eighteen non-ambulatory individuals (mean age = 44 ± 16 years, mean time since injury = 7.8 ± 32.6 years) participated in the study. Poor balance (lower Function in Sitting Test score) was associated with higher odds of future recurrent falls (Odds Ratio = 0.70, 95% CI, 0.48 to 1.00, p = 0.05), area under the receiving operating curve = 0.87, sensitivity = 88%, and specificity = 70%.

CONCLUSIONS

A comprehensive sitting balance assessment that includes the static, proactive, and reactive components of balance with the integration of sensorial functions as evaluated within the Function in Sitting Test may be useful for predicting recurrent falls among non-ambulatory individuals with spinal cord injury. Replication of the findings in a larger sample is warranted.

Prediction of Stability during Walking at Simulated Ship's Rolling Motion Using Accelerometers

Due to a ship's extreme motion, there is a risk of injuries and accidents as people may become unbalanced and be injured or fall from the ship. Thus, individuals must adjust their movements when walking in an unstable environment to avoid falling or losing balance. A person's ability to control their center of mass (COM) during lateral motion is critical to maintaining balance when walking. Dynamic balancing is also crucial to maintain stability while walking. The margin of stability (MOS) is used to define this dynamic balancing. This study aimed to develop a model for predicting balance control and stability in walking on ships by estimating the peak COM excursion and MOS variability using accelerometers. We recruited 30 healthy individuals for this study. During the experiment, participants walked for two minutes at self-selected speeds, and we used a computer-assisted rehabilitation environment (CAREN) system to simulate the roll motion. The proposed prediction models in this study successfully predicted the peak COM excursion and MOS variability. This study may be used to protect and save seafarers or passengers by assessing the risk of balance loss.

Nonlinear Response of Human Trunk Musculature Explains Neuromuscular Stabilization Mechanisms in Sitting Posture

OBJECTIVE

Determining the roles of underlying mechanisms involved in stabilizing the human trunk during sitting is a fundamental challenge in human motor control. However, distinguishing their roles requires understanding their complex interrelations and describing them with physiologically meaningful neuromechanical parameters. The literature has shown that such mechanistic understanding contributes to diagnosing and improving impaired balance as well as developing assistive technologies for restoring trunk stability. This study aimed to provide a comprehensive characterization of the underlying neuromuscular stabilization mechanisms involved in human sitting.

APPROACH

This study characterized passive and active stabilization mechanisms involved in seated stability by identifying a nonlinear neuromechanical physiologically-meaningful model in ten able-bodied individuals during perturbed sitting via an adaptive unscented Kalman filter to account for the nonlinear time-varying process and measurement noises.

MAIN RESULTS

We observed that the passive mechanism provided instant resistance against gravitational disturbances, whereas the active mechanism provided delayed complementary phasic response against external disturbances by activating appropriate trunk muscles while showing non-isometric behavior. The model predicted the trunk sway behavior during perturbed sitting with high accuracy and correlation (average: 0.0007 [rad2] and 86.77%). This allows a better mechanistic understanding of the roles of passive and active stabilization mechanisms involved in sitting.

SIGNIFICANCE

Our characterization approach accounts for the inherently nonlinear behavior of the neuromuscular mechanisms and physiological uncertainties, while allowing for real-time tracking and correction of parameters' variations due to external disturbances and muscle fatigue. The outcome of our research, for the first time, (1) allows a better mechanistic understanding of the roles of passive and active stabilization mechanisms involved in sitting; (2) enables objective evaluation and targeted rehabilitative interventions for impaired balance; facilitate bio-inspired designs of assistive technologies, and (3) opens new horizons in mathematical identification of neuromechanical mechanisms employed in the stable control of human body postures and motions.