Can physiological metrics react to changing fall risk situations?
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Physiological metrics can react to changing fall risk situations. The use of a physiological profile assessment (PPA) can help differentiate individuals who are at risk for falls from those who are not at risk . The PPA involves simple tests of vision, peripheral sensation, muscle force, reaction time, and postural sway, which can be administered quickly and with portable equipment. The results from the PPA can be used to assess an individual's performance in relation to a normative database and target deficits for intervention . Additionally, the use of an implanted cardiac monitor with an embedded tri-axial accelerometer allows for the collection of activity and cardiac data, which can be used to assess falls risk . By examining biophysiological changes in activity levels, posture changes, and cardiac parameters, clinicians can identify trends that may indicate an increased risk of falling . Furthermore, methods and apparatuses have been developed to improve the accuracy of physiological sensor data, such as PPG sensors, through filtering techniques . These techniques adjust the filtered estimate of a physiological metric based on a comparison between instantaneous and current estimates . Remote physiological monitoring can also be used to associate an at-risk falling condition with patient movement data, posture, and activity level, allowing for the issuance of alerts when the at-risk condition is satisfied .
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| Papers (5) | Insight |
|---|---|
| Physiological metrics can react to changing fall risk situations by associating remote monitoring with patient movement data to determine posture and activity levels, issuing alerts when an at-risk condition is detected. | |
| The filtering technique in the paper adjusts physiological metric estimates based on rate limits, potentially aiding in assessing changing fall risk situations by improving accuracy in physiological sensor data processing. | |
| Physiological metrics, including cardiac and activity data from an implantable monitor with an accelerometer, can help detect changing fall risk situations by monitoring biophysiological changes, aiding in predicting and preventing falls. | |
| The paper does not directly address whether physiological metrics can react to changing fall risk situations. | |
| Physiological metrics, such as pulse pressure waves, can react to changing fall risk situations, as indicated by the data acquired in the described method. |
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