Mapping Movement: Applying Motion Measurement Technologies to the Psychiatric Care of Older Adults

Abstract

Clinicians have evaluated motion measurement technologies in older adults with depression, dementia, anxiety, and schizophrenia. Results from studies in dementia populations suggest that motion measurement technologies can assist clinicians in diagnosing dementia earlier through the evaluation of gait, balance, and postural kinematics. Motion detection technologies can also be used to identify mood episodes at an earlier stage by detecting subtle behavioral changes. Clinicians may use the objective data provided by technologies such as accelerometers to identify illnesses earlier, which may inform treatment decisions. The data may be used as a suitable surrogate marker for detecting depression in older adults, predicting the likelihood of falls, or quantifying physical activity in older adults with chronic mental illnesses or anxiety. Motion-based technologies also have the potential to detect physical activity for older adults residing in nursing homes. Wearable technologies are generally well tolerated in older adults, although the use of new technology and electronic health data could involve privacy and security concerns among this vulnerable population.

From Emotions to Mood Disorders: A Survey on Gait Analysis Methodology

“…Several reviews have recently focused on wearable and/or vision-based systems for gait analysis [4], [54], [77]. In particular, Stephens-Fripp et al have reviewed gait data capture in automatic emotion recognition [54], whereas Collier et al and others highlighted the motion measurement technologies for the psychiatric care of elderly patients [36], [78]. In this section, we briefly summarize the main principles behind these systems, as shown in Fig.…”

“…vision algorithms have been developed to extract key-joints in real-time and subsequently estimate gait characteristics [90]- [92]. Although, these systems can accurately be used for gait analysis, activity recognition and energy expenditure estimation, they pose risks to the privacy of the subjects, which limit their acceptance [36].…”

“…Clinical evaluations of all these conditions are subjective and they are based on self-reports, thus, subtle behavioral changes may be unnoticed [36]- [39]. It is also common for subjects with mood disorders to have different behavior at home/work compared to that in the clinic, which further complicates medical assessment [36].…”

“…Clinical evaluations of all these conditions are subjective and they are based on self-reports, thus, subtle behavioral changes may be unnoticed [36]- [39]. It is also common for subjects with mood disorders to have different behavior at home/work compared to that in the clinic, which further complicates medical assessment [36]. Motor abnormalities that reflect the energy and/or biomechanical states of these episodes are evident and they could potentially be used in clinical practice to create objective biomarkers [37]- [39].…”

“…Gait abnormalities in young adults are not confounded by age and thus, they allow better understanding of mood disorders with relation to motor control. There is a consensus that technologies that enable monitoring of locomotion and gait performance would play a significant role in identifying early behavioral changes that could elucidate the underline reasons and shape treatment more effectively [36]- [46].…”