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Identifying balance impairments in people with Parkinson's disease using video and wearable sensors

Identifying balance impairments in people with Parkinson's disease using video and wearable sensors
Identifying balance impairments in people with Parkinson's disease using video and wearable sensors

Background: falls and near falls are common among people with Parkinson's (PwP). To date, most wearable sensor research focussed on fall detection, few studies explored if wearable sensors can detect instability. 

Research question: can instability (caution or near-falls) be detected using wearable sensors in comparison to video analysis?

Methods: twenty-four people (aged 60–86) with and without Parkinson's were recruited from community groups. Movements (e.g. walking, turning, transfers and reaching) were observed in the gait laboratory and/or at home; recorded using clinical measures, video and five wearable sensors (attached on the waist, ankles and wrists). After defining ‘caution’ and ‘instability’, two researchers evaluated video data and a third the raw wearable sensor data; blinded to each other's evaluations. Agreement between video and sensor data was calculated on stability, timing, step count and strategy. 

Results: data was available for 117 performances: 82 (70%) appeared stable on video. Ratings agreed in 86/117 cases (74%). Highest agreement was noted for chair transfer, timed up and go test and 3 m walks. Video analysts noted caution (slow, contained movements, safety-enhancing postures and concentration) and/or instability (saving reactions, stopping after stumbling or veering) in 40/134 performances (30%): raw wearable sensor data identified 16/35 performances rated cautious or unstable (sensitivity 46%) and 70/82 rated stable (specificity 85%). There was a 54% chance that a performance identified from wearable sensors as cautious/unstable was so; rising to 80% for stable movements. 

Significance: agreement between wearable sensor and video data suggested that wearable sensors can detect subtle instability and near-falls. Caution and instability were observed in nearly a third of performances, suggesting that simple, mildly challenging actions, with clearly defined start- and end-points, may be most amenable to monitoring during free-living at home. Using the genuine near-falls recorded, work continues to automatically detect subtle instability using algorithms.

Fall prevention, Imbalance, Parkinson's, Wearable sensors
0966-6362
321-326
Stack, Emma L.
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Agarwal, Veena
a9136686-fe91-4945-a02f-4d129e387197
King, Rachel
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Burnett, Malcolm
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Tahavori, Fatemeh
68d936f9-03bc-44ea-9842-b5687f3f2cb2
Janko, Balazs
5719cee8-1b4c-4b78-b4de-c3e6e7ada942
Harwin, William
a527021a-b0b5-40b0-9a0c-c030b8e75db9
Ashburn, Ann
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Kunkel, Dorit
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Stack, Emma L.
a6c29a03-e851-4598-a565-6a92bb581e70
Agarwal, Veena
a9136686-fe91-4945-a02f-4d129e387197
King, Rachel
ddcb7a86-ada2-4bbf-b69b-919fdd4b1cdd
Burnett, Malcolm
2c3baa00-d368-4ce7-8a8b-822ea7ebe475
Tahavori, Fatemeh
68d936f9-03bc-44ea-9842-b5687f3f2cb2
Janko, Balazs
5719cee8-1b4c-4b78-b4de-c3e6e7ada942
Harwin, William
a527021a-b0b5-40b0-9a0c-c030b8e75db9
Ashburn, Ann
818b9ce8-f025-429e-9532-43ee4fd5f991
Kunkel, Dorit
6b6c65d5-1d03-4a13-9db8-1342cd43f352

Stack, Emma L., Agarwal, Veena, King, Rachel, Burnett, Malcolm, Tahavori, Fatemeh, Janko, Balazs, Harwin, William, Ashburn, Ann and Kunkel, Dorit (2018) Identifying balance impairments in people with Parkinson's disease using video and wearable sensors. Gait & Posture, 62, 321-326. (doi:10.1016/j.gaitpost.2018.03.047).

Record type: Article

Abstract

Background: falls and near falls are common among people with Parkinson's (PwP). To date, most wearable sensor research focussed on fall detection, few studies explored if wearable sensors can detect instability. 

Research question: can instability (caution or near-falls) be detected using wearable sensors in comparison to video analysis?

Methods: twenty-four people (aged 60–86) with and without Parkinson's were recruited from community groups. Movements (e.g. walking, turning, transfers and reaching) were observed in the gait laboratory and/or at home; recorded using clinical measures, video and five wearable sensors (attached on the waist, ankles and wrists). After defining ‘caution’ and ‘instability’, two researchers evaluated video data and a third the raw wearable sensor data; blinded to each other's evaluations. Agreement between video and sensor data was calculated on stability, timing, step count and strategy. 

Results: data was available for 117 performances: 82 (70%) appeared stable on video. Ratings agreed in 86/117 cases (74%). Highest agreement was noted for chair transfer, timed up and go test and 3 m walks. Video analysts noted caution (slow, contained movements, safety-enhancing postures and concentration) and/or instability (saving reactions, stopping after stumbling or veering) in 40/134 performances (30%): raw wearable sensor data identified 16/35 performances rated cautious or unstable (sensitivity 46%) and 70/82 rated stable (specificity 85%). There was a 54% chance that a performance identified from wearable sensors as cautious/unstable was so; rising to 80% for stable movements. 

Significance: agreement between wearable sensor and video data suggested that wearable sensors can detect subtle instability and near-falls. Caution and instability were observed in nearly a third of performances, suggesting that simple, mildly challenging actions, with clearly defined start- and end-points, may be most amenable to monitoring during free-living at home. Using the genuine near-falls recorded, work continues to automatically detect subtle instability using algorithms.

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Accepted/In Press date: 28 March 2018
e-pub ahead of print date: 28 March 2018
Published date: 1 May 2018
Keywords: Fall prevention, Imbalance, Parkinson's, Wearable sensors

Identifiers

Local EPrints ID: 420397
URI: http://eprints.soton.ac.uk/id/eprint/420397
ISSN: 0966-6362
PURE UUID: d7e0c5ee-763c-4e5d-ace3-44a3bd5d032d
ORCID for Veena Agarwal: ORCID iD orcid.org/0000-0002-6904-8243
ORCID for Malcolm Burnett: ORCID iD orcid.org/0000-0002-5481-4398
ORCID for Dorit Kunkel: ORCID iD orcid.org/0000-0003-4449-1414

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Date deposited: 04 May 2018 16:31
Last modified: 17 Dec 2019 05:30

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Contributors

Author: Emma L. Stack
Author: Veena Agarwal ORCID iD
Author: Rachel King
Author: Malcolm Burnett ORCID iD
Author: Fatemeh Tahavori
Author: Balazs Janko
Author: William Harwin
Author: Ann Ashburn
Author: Dorit Kunkel ORCID iD

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