Using accelerations of single inertial measurement units to determine the intensity level of light-moderate-vigorous physical activities: Technical and mathematical considerations.

Quantifying physical activity and estimating the metabolic equivalent of tasks based on inertial measurement units has led to the emergence of multiple methods and data reduction approaches known as physical activity metrics. The present study aims to compare those metrics and reduction approaches based on descriptive and high order statistics. Data were obtained from 147 young healthy subjects wearing inertial measurement units at their wrist or ankle during standing, walking and running, labeled as light, medium or vigorous activities. The research question was, first, if those metrics allowed differentiating between light, moderate, and vigorous physical activities, and, secondly, what was the relationship with the metabolic equivalent of the task performed. The results showed that each metric differentiated the level of activity and presented a high correlation with the metabolic equivalent of the task. However, each metric and data reduction approach demonstrated its specific statistical characteristics related to the localization of the sensors. Our findings also confirm the absolute necessity to detail explicitly all calculus and post processing of metrics in order to quantify the level of activity by inertial measurement units.

Optimized scoring tool to quantify the functional performance during the sit-to-stand transition with a magneto-inertial measurement unit.

BACKGROUND: Sit-to-stand is used as a qualitative test to evaluate functional performance, especially to detect fall risks and frail individuals. The use of various quantitative criteria would enable a better understanding of musculoskeletal deficits and movement strategy modifications. This quantification was proven possible with a magneto-inertial unit which provides a compatible wearable device for clinical routine motion analysis. METHODS: Sit-to-stand movements were recorded using a single magneto-inertial measurement unit fixed on the chest for 74 subjects in three groups healthy young, healthy senior and frail. MIMU data was used to compute 15 spatiotemporal, kinematic and energetic parameters. Nonparametric statistical test showed a significant influence of age and frailness. After reducing the number of parameters by a principal component analysis, an AgingScore and a FrailtyScore were computed. FINDINGS: The fraction of variance explained by the first principal component was 77.48 ±â€¯2.80% for principal component analysis with healthy young and healthy senior groups, and 74.94 ±â€¯2.24% with healthy and frail senior groups. By receiver operating characteristic curve analysis of this score, we were able to refine the analysis to differentiate between healthy young and healthy senior subjects as well as healthy senior and frail subjects. By radar plot of the most discriminate parameters, the motion's strategy could be characterized and be used to detect premature functional deficit or frail subjects. INTERPRETATION: Sit-to-stand measured by a single magneto-inertial unit and dedicated post processing is able to quantify subject's musculoskeletal performance and will allow longitudinal investigation of aging population.

Evaluation of the kinetic energy of the torso by magneto-inertial measurement unit during the sit-to-stand movement.

Sit-to-stand tests are used in geriatrics as a qualitative issue in order to evaluate motor control and stability. In terms of measured indicators, it is traditionally the duration of the task that is reported, however it appears that the use of the kinetic energy as a new quantitative criterion allows getting a better understanding of musculoskeletal deficits of elderly subjects. The aim of this study was to determine the feasibility to obtain the measure of kinetic energy using magneto-inertial measurement units (MIMU) during sit-to-stand movements at various paces. 26 healthy subjects contributed to this investigation. Measured results were compared to a marker-based motion capture using the correlation coefficient and the normalized root mean square error (nRMSE). nRMSE were below 10% and correlation coefficients were over 0.97. In addition, errors on the mean kinetic energy were also investigated using Bland-Altman 95% limits of agreement (0.63 J-0.77 J), RMSE (0.29 J-0.38 J) and correlation coefficient (0.96-0.98). The results obtained highlighted that the method based on MIMU data could be an alternative to optoelectronic data acquisition to assess the kinetic energy of the torso during the sit-to-stand test, suggesting this method as being a promising alternative to determine kinetic energy during the sit-to-stand movement.