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June, 2022
This article was published in the German Newspaper the Handelsblatt. The original title is “Mit KI und Motion-Tracking zur präventiven Medizin“.
Artificial Intelligence (AI) is revolutionizing medicine and care, enhancing diagnostics and patient care. Researchers are leveraging AI in a myriad of ways, such as measuring placental size to detect fetal malnutrition and early detection of blood cancer. Furthermore, AI aids in the development of new drugs and therapies.
An essential aspect of AI application is the use of various information resources, notably patient movement data. These data provide vital clues about a person’s health, from eye movements indicating possible concussions to unique gait patterns hinting at various diseases or impairments.
Particularly in geriatrics and physiotherapy, the intersection of AI and movement data assists in analyzing elderly people’s walking behavior. The fall risk increases with age, and an estimated 2.5 million people aged 85 or older live in Germany. By applying AI-supported solutions such as motion tracking, the individual fall risk can be determined, preventing falls before they occur.
However, there are challenges. The number of caregivers in Germany is dwindling, with around 500,000 professionals projected to be needed by 2035. Current staff faces an increasingly dense workload, leaving less time for individual patient assessments.
To overcome these challenges, AI-based analysis tools could be made available as a smartphone app. These Apps utilize the various sensors or cameras of the phone to perform various analyses. Using data-based learning algorithms, these tools lower the margin of error and further minimize the deviations between the models and reality.
Technology in this format proves useful across the entire medical and care chain, from admission to discharge, orthopedics to physiotherapy.
AI technology could change the face of routine check-ups, with potential for integration into standard care. AI enables proactive medical and care practices, preventing diseases before they become advanced. The technology is available today; the next step is to strengthen its application in practice.
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