Elsevier

Gait & Posture

Volume 31, Issue 2, February 2010, Pages 272-278
Gait & Posture

A body-fixed-sensor-based analysis of power during sit-to-stand movements

https://doi.org/10.1016/j.gaitpost.2009.11.003Get rights and content

Abstract

This study presents an analysis of power exertion for lifting the body's centre of mass (CoM) during rising from a chair. Five healthy young (21–44 years) and 12 healthy older (70–79 years) subjects performed sit-to-stand (STS) movements while data were measured with force-plates underneath chair and feet and motion sensors attached to different locations on the upper and lower trunk. Force-plate-data were used to determine the timing of STS movements and the vertical power for lifting the CoM from a sitting to a standing position. Data of three-dimensional hybrid motion sensors, consisting of accelerometers, gyroscopes and earth-magnetic-field sensors, were used to determine vertical accelerations and power. The comparison of sensor-based estimations of peak power with peak power calculated from force-plate-data demonstrated fair to excellent linear relationships for all sensor locations on the trunk. The best approximation of peak power was obtained by a weighted combination of data measured at different trunk locations. Results of the older subjects were consistent with those of the young subjects performing slow, normal and fast STS movements. The presented approach is relevant for monitoring fall risk and assessment of mobility in older people. Similar approaches for assessing power may be developed for other mobility related activities, such as stair walking, or sports related activities such as jumping.

Introduction

Muscle power, i.e. the speed with which muscular forces produce movements of body segments, is a determinant of the successful performance of sportive activities such as high jump, javelin throw, or weight lifting. However, also the performance of activities in daily life requires that enough muscle power is generated. The safe performance of mobility related activities, such as rising from a chair, walking and stair climbing, requires a control of position and orientation of body segments whilst the body's centre of mass (CoM) is moved from one position to the other. The ability to quickly produce sufficient muscle force is of paramount importance for controlling CoM movements during mobility related activities, and studies demonstrate that decreased muscle strength and/or power is associated with functional limitations [1], [2].

In older people, loss of muscle strength is a strong predictor of falls. Falls are one of the largest health risk factors in older people and they can have serious consequences regarding both physical functioning (e.g. fractures) and psycho-social functioning (e.g. fear of falls leading to activity restriction and social isolation). Fall prevention requires an early identification of fall risk and the use of effective and targeted fall prevention strategies. Measures of muscle strength and balance performance are early indicators of fall risk [3], and studies of exercise-based interventions have shown that combinations of strength and balance training can reduce the risk of falling in older people [4]. Available field tests for assessing balance and mobility usually yield very basic parameters such as movement duration and speed, therefore objective methods that assess additional relevant aspects of movement performance may contribute to fall prediction and/or outcome assessment in older people.

A recent development is the use of body-fixed motion sensors for assessing motor functioning. Though suitable methods for assessing mobility related activities based on the use of motion sensors are available [5], these methods have not yet been applied to their full potential in older people [6]. Moreover, feasible methods to assess muscle strength or power during daily activities are missing. Currently, such measures can only be obtained by using a motion analysis system and/or force-plate in a laboratory environment, or by using devices which usually have been developed for assessing sports related performance in younger subjects or athletes (e.g. cycling or rowing ergometers). Thus, it would be an enormous advance if, in addition to other aspects, power can be assessed during mobility related activities. Particularly, the performance of the sit-to-stand (STS) transfer is very relevant in this respect. The STS transfer is a regular mobility related activity in daily life, it is performed multiple times a day, and studies have demonstrated that measures of STS performance are important indicators of overall functioning and balance performance in older persons [7], [8].

Assuming that trunk kinematics can be used to approximate CoM movement, this paper analyses whether the power to lift the body's CoM during the STS movement can be determined based on motion sensors on the trunk. The most critical aspect in this approach is an accurate estimation of vertical CoM accelerations. Therefore, hybrid sensors, consisting of accelerometers, gyroscopes, and magnetometers, were used to calculate vertical accelerations. Subsequently, power was calculated from vertical accelerations at each trunk location and from vertical accelerations of a virtual CoM position which was estimated by a weighted average of acceleration data. To evaluate the sensor-based approaches, a comparison was made to data obtained by a conventional laboratory approach; i.e. a camera-based motion analysis system in combination with two force-plates under chair and feet.

Section snippets

Methods

Seventeen healthy subjects participated in this study. Before participating, subjects received information about the nature of the study. All participants signed an informed consent. The Medical Ethical Committee of the University Medical Center Groningen approved of the study.

Results

To avoid that loss of data packets affected data analysis, trials were excluded for further analysis if data samples were missing. The remaining trials comprised 16 slow, 20 natural, 22 fast and 20 STS movements with use of arm rest in the young subjects, and 32 STS movements at a natural speed in the older subjects. Without explicit instructions the young subjects never used an arm rest. In the older subjects, only one subject used arm rests in 2 out of 3 STS measurements.

Discussion

This study analyzed power exertion during STS based on motion sensors. To this purpose, young subjects were asked to perform different STS movements, and healthy older (70+) subjects were asked to stand up from a chair at a preferred speed. The instructions to the young subjects lead to a marked range of STS performances; mean movement durations varied between 0.88 and 2.52 s. Mean STS duration of the older subjects was close to mean STS duration of young subjects at their preferred speed, i.e.

Conflict of interest statement

The authors declare that they have no conflicts of interest.

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