Motion Signal Processing in Heel Rise Tests Applied to Older Adults
Palavras-chave:
calf raise, inertial sensors, integration drift, smartphoneResumo
The aging of the global population is a growing reality. It is estimated that the number of people over the age of 60 will reach 2 billion worldwide by 2050. In older adults, the muscular function of the triceps surae plays a central role in postural control and functionality, being essential for maintaining balance and mobility. Reduced performance of the plantar flexor muscles has been associated with losses in functionality, decreased quality of life, and an increased risk of falls, making the assessment of this muscle group crucial. In this context, the Heel Rise Test (HRT) has been used to evaluate strength and endurance. Traditional assessment methods for this test are based on visually counting repetitions, which may lack accuracy. Moreover, the identification of other relevant movement parameters, particularly those related to the time and frequency domains, is often overlooked. On the other hand, inertial sensors embedded in smartphones represent a promising alternative for quantifying translational acceleration and angular velocity signals, given their low cost and large accessibility. However, the use of such signals requires caution, as double integration of acceleration signals to obtain displacement data may lead to cumulative errors, known as integration drift. This study presents the development of a reliable and effective numerical procedure for processing inertial sensor signals from smartphones during the Heel Rise Test. The measurements obtained through the proposed procedure are compared to those acquired simultaneously by using reference methods (such as video cameras), ensuring concurrent validity. The results indicate that the proposed procedure provides sufficiently accurate measurements, enabling the extraction of relevant information about the muscular function of plantar flexors in clinical settings. It is understood that access to reliable and easily obtainable data can positively impact the diagnosis and monitoring of the target muscular function, supporting strategies aimed at reducing the risk of falls and improving quality of life in older adults.Publicado
2025-12-01
Edição
Seção
Artigos