Digital Health Technologies for Optimising Treatment and Rehabilitation Following Surgery: Device-Based Measurement of Sling Posture and Adherence
Background: Following shoulder surgery, controlled and protected mobilisation for an appropriate duration is crucial for appropriate recovery. However, methods for objective assessment of sling wear and use in everyday living are currently lacking. In this pilot study, we aim to determine if a sling...
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MDPI AG
2024-12-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/1/166 |
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| author | Joss Langford Ahmed Barakat Engy Daghash Harvinder Singh Alex V. Rowlands |
| author_facet | Joss Langford Ahmed Barakat Engy Daghash Harvinder Singh Alex V. Rowlands |
| author_sort | Joss Langford |
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| description | Background: Following shoulder surgery, controlled and protected mobilisation for an appropriate duration is crucial for appropriate recovery. However, methods for objective assessment of sling wear and use in everyday living are currently lacking. In this pilot study, we aim to determine if a sling-embedded triaxial accelerometer and/or wrist-worn sensor can be used to quantify arm posture during sling wear and adherence to sling wear. Methods: Four participants were asked to wear a GENEActiv triaxial accelerometer on their non-dominant wrist for four hours in an office environment, and, for two of those hours, they also wore a sling in which an additional GENEActiv accelerometer was secured. During sling wear, they were asked to move their arm in the sling through a series of pre-specified arm postures. Results: We found that upper arm angle and posture type during sling wear can be predicted from a sling sensor alone (R<sup>2</sup> = 0.79, <i>p</i> < 0.001 and Cohen’s kappa = 0.886, respectively). The addition of a wrist-worn sensor did not improve performance. The optimisation of an existing non-wear algorithm accurately detected adherence (99.3%). Conclusions: the remote monitoring of sling adherence and the quantification of immobilisation is practical and effective with digital health technology. |
| format | Article |
| id | doaj-art-d53c27420fd34cb9b531a48591cd2942 |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-d53c27420fd34cb9b531a48591cd29422025-01-10T13:21:06ZengMDPI AGSensors1424-82202024-12-0125116610.3390/s25010166Digital Health Technologies for Optimising Treatment and Rehabilitation Following Surgery: Device-Based Measurement of Sling Posture and AdherenceJoss Langford0Ahmed Barakat1Engy Daghash2Harvinder Singh3Alex V. Rowlands4ActivInsights Ltd., 6 Nene Road, Bicton Industrial Park, Kimbolton, Huntingdon PE28 0LF, UKTrauma & Orthopaedics Department, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UKTrauma & Orthopaedics Department, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UKTrauma & Orthopaedics Department, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UKAssessment of Movement Behaviours (AMBer), Leicester Lifestyle and Health Research Group, Diabetes Research Centre, University of Leicester, Leicester LE5 4PW, UKBackground: Following shoulder surgery, controlled and protected mobilisation for an appropriate duration is crucial for appropriate recovery. However, methods for objective assessment of sling wear and use in everyday living are currently lacking. In this pilot study, we aim to determine if a sling-embedded triaxial accelerometer and/or wrist-worn sensor can be used to quantify arm posture during sling wear and adherence to sling wear. Methods: Four participants were asked to wear a GENEActiv triaxial accelerometer on their non-dominant wrist for four hours in an office environment, and, for two of those hours, they also wore a sling in which an additional GENEActiv accelerometer was secured. During sling wear, they were asked to move their arm in the sling through a series of pre-specified arm postures. Results: We found that upper arm angle and posture type during sling wear can be predicted from a sling sensor alone (R<sup>2</sup> = 0.79, <i>p</i> < 0.001 and Cohen’s kappa = 0.886, respectively). The addition of a wrist-worn sensor did not improve performance. The optimisation of an existing non-wear algorithm accurately detected adherence (99.3%). Conclusions: the remote monitoring of sling adherence and the quantification of immobilisation is practical and effective with digital health technology.https://www.mdpi.com/1424-8220/25/1/166shoulderslingadherenceaccelerometersurgerywrist |
| spellingShingle | Joss Langford Ahmed Barakat Engy Daghash Harvinder Singh Alex V. Rowlands Digital Health Technologies for Optimising Treatment and Rehabilitation Following Surgery: Device-Based Measurement of Sling Posture and Adherence Sensors shoulder sling adherence accelerometer surgery wrist |
| title | Digital Health Technologies for Optimising Treatment and Rehabilitation Following Surgery: Device-Based Measurement of Sling Posture and Adherence |
| title_full | Digital Health Technologies for Optimising Treatment and Rehabilitation Following Surgery: Device-Based Measurement of Sling Posture and Adherence |
| title_fullStr | Digital Health Technologies for Optimising Treatment and Rehabilitation Following Surgery: Device-Based Measurement of Sling Posture and Adherence |
| title_full_unstemmed | Digital Health Technologies for Optimising Treatment and Rehabilitation Following Surgery: Device-Based Measurement of Sling Posture and Adherence |
| title_short | Digital Health Technologies for Optimising Treatment and Rehabilitation Following Surgery: Device-Based Measurement of Sling Posture and Adherence |
| title_sort | digital health technologies for optimising treatment and rehabilitation following surgery device based measurement of sling posture and adherence |
| topic | shoulder sling adherence accelerometer surgery wrist |
| url | https://www.mdpi.com/1424-8220/25/1/166 |
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