The Assure system uses a movement sensor that constantly monitors the movement of the wristband. It can be configured to detect movement patterns that could be a fall. Every fall is different and the Assure will never detect 100% of falls with no false alarms. There are various settings to suit most people’s needs.
To configure fall detection use the drop down list. Most users will find one of the four presets suitable:
Figures from AgeUK suggest that about one third of all people over 65 fall each year. If the fall occurs whilst the person is home alone and the fall results in the person being unable to move, the consequences can be very serious. The Assure uses advanced algorithms that detect movement patterns that could be a fall
If the fall monitor detects a potential fall, it will monitor for a period of inactivity afterwards before starting the usual pre-alert checks. The wearer can cancel the alert in the usual way by either pressing a single button on the band or answering the confirmation phone call and pressing ‘1’.
It is important to note that the fall detection is always confirmed by a period of inactivity. In 'Day' mode (see below) there will be a delay ranging from 45 seconds to 8 minutes, depending on your settings, between a fall and an alert being raised.
During sleep most people naturally change position then remain still. This can be interpreted as a fall resulting in an unwelcome false alert in the middle of the night. Day/Night mode extends the inactivity period to 4 hours during the night (9 at night until 7 the following morning). This period has been selected to be longer than the period of deep sleep for the majority of people.
As with any other wrist-worn device, using movement as a method of detecting falls can never be 100% reliable. There will always be a compromise between valid detections and false alarms. One of the most common false alarm activations occurs when the wearer is getting into bed where there can be a sudden movement followed by a long period of inactivity which is very difficult to distinguish from a genuine fall.
Fall detection has three distinct phases:
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