Musculoskeletal conditions-;which encompass impairments of the joints, bones, or muscles-;affect greater than 1.5 billion people around the globe. Like most health problems, catching these issues early could potentially prevent serious disorders, but few quantitative and objective tests to evaluate musculoskeletal health can be found.

There’s a major need for cheap, scalable tools to objectively measure and monitor changes in physical function, especially as the worldwide population ages. Finding ways to remotely evaluate musculoskeletal health could assist diagnoses, guide treatment decisions, and potentially improve the standard of lifetime of countless people.”

Melissa Boswell, Ph.D., Postdoctoral Fellow at Stanford University

To tackle this problem, Boswell and colleagues developed a web based tool that may analyze self-collected, at-home videos taken with a smartphone. The tool, which was deployed in a nationwide study, was sensitive enough to predict physical health (as evaluated using a standardized survey tool) and osteoarthritis of the knee or hip. Results of the study were recently described in npj Digital Medicine (a publication of Nature).

The tool relies on the sit-to-stand test, an evaluation that’s fairly self-explanatory: ranging from a seated position with arms crossed, a participant stands up and sits back down a complete of 5 times while being timed. Slower times could indicate reduced lower body strength, or a condition that affects the musculoskeletal system, or just aging, explained Boswell, noting that the test by itself isn’t a precise measure of physical function. That is where kinematic analyses (which evaluate motion) come into play. By assessing things just like the angles and accelerations of various parts of the body during movement, more definitive predictions of musculoskeletal health could be made.

Here’s how their tool works-;using a smartphone, someone takes a video of the participant performing the sit-to-stand test, which is then uploaded into the app. The tool combines an open-source algorithm for estimation of the participant’s pose with customized algorithms that calculate the time it takes for the participant to finish the test together with kinematic aspects, akin to joint angles during movement. Participants also take a survey to input demographic information and complete a questionnaire to judge aspects like fatigue, pain, emotional distress, and overall physical function. Participants were also asked in the event that they had a previous clinical diagnosis of osteoarthritis.

Since the study was accessible to many individuals, participation was markedly higher than traditional biomechanics trials. “Investigations of human movement have typically been limited to biomechanics laboratories equipped with expensive and technical equipment,” Boswell explained. Of their nationwide study, Boswell and colleagues incorporated data from 405 participants from 35 U.S. states, with individuals submitting videos in only over a month’s time. “Our study had greater than 35 times the median variety of subjects compared with traditional biomechanics studies,” she noted. The age of the participants ranged from 18 to 96 years, with a mean age of 37.5 years.

Much like previous laboratory and clinical assessments, the researchers found that a bigger maximum trunk angle-;that’s, leaning further forward-;when standing could predict osteoarthritis, even when controlling for quite a lot of aspects, akin to age, sex, or body mass index (BMI). Like previous biomechanical studies, the tool found that longer times to finish the sit-to-stand test were related to a lower physical health rating, the next BMI, and older age. These results suggest that at-home smartphone-based assessments could also be feasible for future biomechanical studies.

Because their trial had a various participant population, the researchers were capable of evaluate how demographic aspects may be related to biomechanical differences. After they compared the 2 largest ethnic groups of their study, they found that the 243 white participants had significant differences in trunk angle throughout the sit-to-stand test compared with the 103 Asian participants, even after taking other variables into consideration. “This finding indicates that we will not assume similarities across racial and ethnic groups and highlights the importance of more diverse samples in biomechanical studies,” said Boswell. “These functional differences are likely as a consequence of underlying aspects like mobility or strength, and even health inequities, that weren’t captured on this study.”

The researchers also found a biomechanical feature (specifically, leaning forward more quickly when standing) that was significantly related to the next mental health rating. “It’s exciting to see potential relationships between mental health and the way we move,” Boswell said. She stressed, nevertheless, that the relationships between biomechanical differences and race/ethnicity or mental health status observed of their study are mainly hypothesis-generating and would require follow-up research.

“This study highlights that self-collected data could be used to evaluate physical function and musculoskeletal health, allowing patients to take part in a biomechanical study from the comfort of their very own home,” said Moria Bittmann, Ph.D., a program director within the division of Discovery Science & Technology on the National Institute of Biomedical Imaging and Bioengineering (NIBIB). “Studies like these provide additional evidence that smartphone-based applications will help facilitate decentralized clinical trials and might empower individuals to take an energetic role of their health.”

“Recent and improved machine learning tools are always being developed to estimate human motion (and rather more), which have the potential to have a profound impact on health care through mobile health monitoring,” said senior study creator Scott Delp, Ph.D., a professor at Stanford University and director of the NIH-funded Mobilize Center. “But merely constructing latest AI tools isn’t enough. To actually make an impact, we’d like to translate these latest tools into the world, make them usable for the common person and for vulnerable populations, and rigorously evaluate their ability to provide insights into necessary clinical measures.”

This study was supported by the Mobilize Center, which is funded by a grant from NIBIB and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD; P41EB027060) and the Restore Center, a Medical Rehabilitation Research Resource that’s supported by NICHD and the National Institute of Neurological Disorders and Stroke (NINDS; P2CHD101913). This study also received support from the National Science Foundation (DGE-1656518).

Source:

National Institute of Biomedical Imaging and Bioengineering

Journal reference:

Boswell, M. A., et al. (2023). Smartphone videos of the sit-to-stand test predict osteoarthritis and health outcomes in a nationwide study. Npj Digital Medicine. doi.org/10.1038/s41746-023-00775-1.