Gait sensor could detect Alzheimer’s, identify fall risk

Newcastle University’s Lynn Rochester has studied the use of wearable sensors to identify walking characteristics as clinical biomarkers for Alzheimer’s Disease.  The same sensors can detect gait changes that require intervention to prevent falls and prolong independence.

According to Rochester, “free-living gait analysis at home is particularly useful as it allows objective observation of an individual’s day-to-day activity. It also has the benefit of providing continuous data over a prolonged time that may be more sensitive than one-off assessments.”

She believes that continuous walking sensors could make clinical trials more efficient, and support clinician decisions.


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