Researchers at the University of Missouri are testing a system that pairs in-home sensors with artificial intelligence to track functional changes in people with amyotrophic lateral sclerosis (ALS). Bill Janes leads the project to adapt devices first developed by Marjorie Skubic and Marilyn Rantz for monitoring older adults. Those sensors can detect shifts in behavior and physical activity, including walking and sleeping patterns, which previously helped prompt interventions.
Sensor signals travel wirelessly from the home through two small boxes and then transfer securely to university systems for analysis. The research team uses machine learning to build models that estimate a patient's score on the ALS Functional Rating Scale Revised (ALSFRS-R), a clinical measure of daily abilities such as walking, talking, swallowing and breathing. The group is now verifying that sensor data reflect real-world changes in daily function; after validation they will move into predictive modeling to interpret the collected data.
Noah Marchal leads the data science work, implemented with his advisor Xing Song. The aim is to detect concerning changes in gait or respiration before they cause a fall or hospitalization. The team plans to integrate the predictive model into clinical workflows so clinicians can receive alerts and then check in with patients, adjust medication, recommend assistive devices, or suggest further treatment.
Early feedback from participating families has been positive, with many reporting greater connection and peace of mind. The researchers note the same approach could be adapted to monitor other chronic conditions such as Parkinson’s disease or heart failure. The study appears in the journal Frontiers in Digital Health and was reported by the University of Missouri.
Difficult words
- sensors — device that detects physical or environmental signals
- monitor — observe or check a condition over timemonitoring
- machine learning — computer methods that learn patterns from data
- predictive — used to forecast what will happen next
- verifying — check that something is true or accurate
- gait — a person's way of walking or moving
- respiration — the process of breathing in and out
- interventions — an action to improve a person's condition
Tip: hover, focus or tap highlighted words in the article to see quick definitions while you read or listen.
Discussion questions
- What are the main benefits and possible concerns of using in-home sensors and AI to monitor people with chronic conditions? Give reasons based on the text.
- How could the same sensor and AI approach be useful for other chronic conditions such as Parkinson’s disease or heart failure? Give examples.
- How might integrating predictive alerts into clinical workflows change the way clinicians care for patients? Explain possible positive and negative effects.
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