While strategies to prevent fall incidents exist, very few vulnerable patients present themselves to a doctor for fall prevention and not many clinicians are able to detect fall risk by eye. Subtle, yet noticeable, movement patterns in the walking cycle can be recognised by a smartphone. Once recorded, these movements are analysed using machine recognition and graded upon likeliness of falling. By relying on timely detection of these aberrant movements, the patient can be diagnosed and helped before the incident occurs.
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