In a prior post, I’d written about results from a National Health & Aging Trends Study (NHATS), led by researchers at John Hopkins University and the University of Michigan. The study has been ongoing since 2011 and seeks to investigate how daily life activities change for older adults as we age. There are many findings summarized from the study; however, it is the reported changes in mobility by age related findings that I find most interesting.
According to the NHATS results, the percentage of aged 72+ non nursing home resident adults categorized as fully able to carry out mobility activities declined by approximately 6% from 2011 to 2021. However the percentage of adults in this same category experiencing successful mobility , given access to a mobility device, increased by approximately 8% over the same period. This reads like fairly good news and suggests that seasoned adult access to and usage of mobility devices could potentially aid in our ability to experience mobility independence while attempting to age in place.
AI Technology and Mobility Support
Available for our use are traditional mobility devices we are accustomed to such as canes, wheel chairs, walkers, and crutches as well as many other device types. However, it has been interesting to me to also learn that artificial intelligence (AI) technology is greatly enhancing our benefits to using mobility devices by supporting real-time monitoring of our mobility activity level trends and changes.
Many productive mobility device support solutions have been implemented using AI technology; however, I wanted to take a moment to focus on the use of wearable AI technology in support of mobility management needs. I learned that there are AI-driven wearable devices that can monitor and report real-time changes in our mobility activity levels. That is, such devices can serve as a means of sending alerts to our medical professionals and caregivers when something is found to be potentially amiss. If instance, alerts may generate when the AI-technologies detect abnormal changes in our mobility activities. Sounds really awesome; and, this is clearly a data driven AI solution. And, its implementation supports actions that have been shown to be beneficial to maintaining our seasoned adult community mobility independence as we age.
Wearables and Data Quality
However, given that successful implementation of an AI-based mobility tracking wearable support device is dependent on data, then there are typical data quality concerns for consideration. Given the potentially high-stakes decisions that are to be made (or not made) , it is important to have accuracy and precision in the reported data and interpretation of the results.
According to a National Institute of Health (NIH) National Library of Medicine study, there are actually a number of factors that could potentially impact the quality collection and interpretation of data obtained from wearable devices. These factors could encompass hardware, software, connectively, and even human generated data reporting and usage errors. Errors associated with these factors, if not accounted for, could potentially lead to misleading interpretations of reported results.
So, it is good that we seasoned adults can look to depend on the monitoring and tracking of mobility data, via an AI-based wearable device support solution, to aid our aging in place desires. And as a consequence, it is also important for us to be concerned with supporting and encouraging meaningful efforts that are focused on ensuring that the captured data from wearable devices is of an acceptable level of quality.
To this end, I will be delivering a number of training sessions overviewing concerns and detailing reported solution oriented approaches to maintaining wearable data quality and integrity levels. Stay connected and stay informed.
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