Motion and Stability in Older Adults

As we become older, movement becomes slower and more difficult. At some point, people become dependent on assistance to perform daily tasks. But assistive devices and intelligent technologies could also help to support older adult to maintain their mobility or even keep their active life style. To understand the actual needs of different groups of older adults in terms of assistance, biomechanical motion studies are carried out in the Heidelberg Center for Motion Research (HCMR). With the motion capture system, ground-embedded force plates, muscle activity sensors, pressure shoe insoles and a safety harness to prevent falls, the HCMR movement lab provides optimal conditions to study movement in older adults and evaluate the provided support by assistive devices. In addition, studies with an exergame-based balance platform are being performed to identify training needs of different groups of older adults and develop adaptive exergame-based balance training programs.

We are looking for young and older participants to join our motion studies. See our flyer!

Motion analysis in Older Adults

Daily activities are becoming increasingly more difficult as we become older, due to reduced muscle power, impaired motor control, delayed response time and decreased cognitive capacity. This often leads to reduced functional ability, but also often results in falls and injuries. This project (A1: “Quantitative analysis of mobility change and movement stability in old age”) focuses on measuring the changes that occur in movement and stability during aging. More specifically, we are interested in how mobility is affected in older adults of different functional ability, or frailty levels. A selection of supportive devices is available to increase the mobility in the more frail older adults, such as rollators to support walking. It is, however, unknown how these devices support movement. This subproject aims to analyze the interaction between older adults and assistive devices, to accelerate the development of intelligent supportive devices specifically targeted to older adults need. Within the project, we focus on studying walking, standing balance and sit-to-stand movement in older adults of different frailty levels, ranging from older adults who want to maintain their actively lifestyle to those who depend on support for daily activities.

We first focused on collecting sit-to-stand data in a group of younger and a group of older adults, measuring movement of the body with motion capture markers and the forces exerted underneath the feet. We study different strategies of standing up, for instance with and without swing of the arms. The next step is to study the effect of providing assistance: to see if devices would support older adults with muscle weakness to stand up easier by reducing the loading on the knees. In addition, we aim to see to what extent devices provide stability for those with impaired coordination and stability.

Detection of (in)stability in Older Adults

The ability to maintain balance during everyday activities declines with age and results in a great deal of injury. It is difficult to overstate the magnitude of injury caused by falling: in many developed countries the amount of injury caused by falling is second only to motor vehicle accidents. While balance aids can help, the best assistance is still offered by a human caregivers because they can simultaneously monitor a subject’s balance and provide assistance to prevent a fall. Unfortunately, not everyone who needs a caregiver has access to one.

To address this problem, we are focusing in this project (A2: “Algorithmic basics for analyzing and improving the stability of movements”) on developing a balance monitoring system that will observe a subject’s body and assess the stability of their movement. To achieve this aim, this project will focus on two challenging tasks: measuring the pose of the subject’s body using compact sensors, and translating this measurement into a real-time balance assessment. If successful, this project will greatly improve the intelligence of balance aids and hopefully reduce a lot of needless injury.

Exergame-based balance training in Older Adults

Everyday life involves numerous situations in which a balance task has to be performed simultaneously with a second cognitive tasks (e.g., standing in a moving tram while having a conversation). However, the ability to control balance under such dual-task conditions deteriorates with age. Because an impaired dual-task balance performance substantially increases the risk of falling and thus poses mobility limitations, effective intervention strategies to improve this performance are highly relevant in older age. Exercise-based videogaming, also called exergaming, provides a unique and exciting opportunity to combine balance exercises with cognitive-challenging tasks in an interactive game-based approach. As positive effects of exergaming on relevant health outcomes (e.g., balance, dual-tasking, mobility, fall risk) have been reported and the playful character of exergames can help to enhance older people’s motivation toward exercise adherence, the use of exergame-based balance training systems in prevention and rehabilitation program for older adults is increasing exponentially.

A highly innovative development in exergames is to use the internal data stream to evaluate the specific performance level of an individual, to adjust the difficulty of exergame task accordingly, and to depict the training progress in detail. This project (B5: “Exergames to increase mobility and stability”) aims to take this development a step further. Based on the internal data stream of an exergame-based balance training system and 3D motion capture data of a subject’s body movements, we aim to identify individual motor and/or cognitive-related errors (error patterns and hierarchies) during exergame play. This data will be used to develop more intelligent exergames for the training system that adapt the difficulty level in real-time during the exergame to the current performance or specific errors of the individual subject. Such intelligent exergame-based balance platform is still missing in the exergame development and has the potential to provide a highly effective training tool for improving balance and mobility as well as reducing the fall risk in older adults by specifically addressing their individual limitations and resources.