Accelerometer assessed upper limb activity in people with stroke: a validation study considering ambulatory and non-ambulatory activities

Bezuidenhout, Lucian; Joseph, Conran; Einarsson, Ulrika; Thurston, Charlotte; Hagströmer, María; Conradsson, David

doi:10.1080/09638288.2021.2012838

Cited by 8 publications

(17 citation statements)

References 35 publications

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“…One study was excluded due to poor methodological quality, scoring only four points ( Supplementary Materials ). Out of the remaining 32 studies that were included for data synthesis, 29 (91%) were of high quality [ 5 , 8 , 9 , 10 , 11 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ] and three (9%) of moderate quality [ 43 , 44 , 45 ]. This inclusion process is described in Figure 1 .…”

Section: Resultsmentioning

confidence: 99%

“…In total 1076 stroke patients were included in the 32 studies, ranging from four to 169 stroke patients per study. Ten studies included data of in total 236 healthy controls in their analysis [ 5 , 8 , 20 , 23 , 29 , 33 , 35 , 36 , 40 , 44 , 45 ]. The reported average age of the stroke participants was 61 years while healthy participants were usually younger with a reported average of 55.8 years.…”

Section: Resultsmentioning

confidence: 99%

“…Reported Time After Stroke (TAS) was highly different between studies: five studies took place during the acute phase of stroke [ 33 , 38 , 40 , 42 , 43 ]—less than a week, as defined by Bernhardt et al [ 46 ]—another eight included patients during the early sub-acute phase [ 5 , 10 , 21 , 22 , 25 , 30 , 34 , 39 ] and eleven focused on chronic stroke patients [ 8 , 9 , 11 , 20 , 26 , 27 , 28 , 29 , 36 , 41 , 44 ]. The remaining articles included patients which were in different phases after stroke onset: acute and early sub-acute [ 23 , 24 ], early-subacute and late subacute [ 19 ], late sub-acute and chronic [ 35 ] or early, late and chronic phase [ 31 , 32 , 37 , 45 ]. See Appendix A for details.…”

Section: Resultsmentioning

confidence: 99%

“…Most of the studies—26 of 32—focused their research exclusively on upper limb functioning and placed the sensors on the wrists or forearms, while twelve of these studies also placed sensors on other parts of the body [ 10 , 19 , 20 , 26 , 29 , 31 , 32 , 35 , 36 , 39 , 43 , 44 ]. Except for the studies [ 29 , 44 ], in which the (electrohydraulic) sensors were placed along the arm, from shoulder to wrist, and [ 36 ] in which a magnetic ring was used as part of the setup, the information of the additional sensors was used to derive parameters for full body kinematic models [ 31 , 32 ], activity recognition or gait detection [ 10 , 19 , 20 , 26 , 35 , 39 ]. Four studies combined upper and lower body data [ 5 , 34 , 37 , 43 ], and three focused on walking only, in particular on the amount, number of walking bouts and gait characteristics [ 11 , 21 , 23 ].…”

Section: Resultsmentioning

confidence: 99%

“…Most of the upper limb activity related movement measures were based on the magnitude of the 3D accelerometer vector

. Several studies [ 5 , 8 , 9 , 10 , 19 , 20 , 22 , 24 , 25 , 28 , 30 , 35 , 36 , 39 , 40 , 41 , 42 , 43 ] integrated this value over a time window -ranging from a few seconds [ 8 ] to several hours [ 10 ]- to quantify the amount and intensity of upper limb movement. Studies that reported their findings using similar values, like the signal magnitude area [ 34 ], or ‘counts’ are also included in this category.…”

Section: Resultsmentioning

confidence: 99%

See 4 more Smart Citations

Quantification of Movement in Stroke Patients under Free Living Conditions Using Wearable Sensors: A Systematic Review

Quirós

Douma

Akker‐Scheek

et al. 2022

Sensors

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Stroke is a main cause of long-term disability worldwide, placing a large burden on individuals and health care systems. Wearable technology can potentially objectively assess and monitor patients outside clinical environments, enabling a more detailed evaluation of their impairment and allowing individualization of rehabilitation therapies. The aim of this review is to provide an overview of setups used in literature to measure movement of stroke patients under free living conditions using wearable sensors, and to evaluate the relation between such sensor-based outcomes and the level of functioning as assessed by existing clinical evaluation methods. After a systematic search we included 32 articles, totaling 1076 stroke patients from acute to chronic phases and 236 healthy controls. We summarized the results by type and location of sensors, and by sensor-based outcome measures and their relation with existing clinical evaluation tools. We conclude that sensor-based measures of movement provide additional information in relation to clinical evaluation tools assessing motor functioning and both are needed to gain better insight in patient behavior and recovery. However, there is a strong need for standardization and consensus, regarding clinical assessments, but also regarding the use of specific algorithms and metrics for unsupervised measurements during daily life.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…Most of the upper limb activity related movement measures were based on the magnitude of the 3D accelerometer vector

Section: Resultsmentioning

confidence: 99%

See 3 more Smart Citations

Quantification of Movement in Stroke Patients under Free Living Conditions Using Wearable Sensors: A Systematic Review

Quirós

Douma

Akker‐Scheek

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

Clinical research on neurological and psychiatric diagnosis and monitoring using wearable devices: A literature review

Huang,

Wang,

et al. 2024

Interdisciplinary Medicine

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Wearable devices have opened up exciting possibilities for monitoring and managing home health, particularly in the realm of neurological and psychiatric diseases. These devices capture signals related to physiological and behavioral changes, including heart rate, sleep patterns, and motor functions. Their emergence has resulted in significant advancements in the management of such conditions. Traditional clinical diagnosis and assessment methods heavily rely on patient reports and evaluations conducted by healthcare professionals, often leading to a detachment of patients from their home environment and creating additional burdens for both patients and healthcare providers. The increasing popularity of wearable devices offers a potential solution to these challenges. This review focuses on the clinical utility of wearable devices in diagnosing and monitoring neurological and psychiatric diseases. Through research findings and practical examples, we highlight the potential role of wearable devices in diagnosing and monitoring conditions such as autism spectrum disorder, depression, epilepsy, stroke prognosis, Parkinson's disease, dementia, and other diseases. Additionally, the review discusses the benefits and limitations of wearable devices in clinical applications, while highlighting the challenges they face. Finally, it provides prospects for enhancing the value of wearable devices in the monitoring and diagnosis of neurological and psychiatric diseases.

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The use of accelerometers to assess upper limb function in patients with obstetric brachial plexus palsy

Leypold,

Bahm,

Schäfer

et al. 2024

Sci Rep

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For half a century, the Mallet Scale (MS) has been utilized to assess upper limb function in patients with obstetric brachial plexus palsy (OBPP). However, the correct use of the MS requires trained personnel and the MS does not measure compensatory movements. For this reason, new methods are needed to compensate for these weaknesses. This study introduces an innovative method for objective functional motion analysis using accelerometers to measure upper limb movements in thirty patients with obstetric brachial plexus lesions. Five triaxial accelerometers were positioned on the chest and each upper limb. They recorded acceleration signals during repetitive everyday tasks: hand-to-mouth (HM), hand-to-neck (HN), and hand-to-spine (HS). From these signals, 54 features were extracted and subjected to linear correlation tests to identify 5 suitable features. An algorithm was then developed to categorize patients into five groups and compute an individual movement performance score (iMPScore) assessing the patient’s upper extremity function. By using the iMPScore more than 75% of all participants have been classified correctly with respect to their MS category. Identification of MS I category patients in general and assessing upper extremity function of MS I to III in HS tasks were most challenging. We conclude that the introduced approach is a valuable tool for gauging movement limitation of upper limbs in patients with obstetric brachial plexus palsy. Compared to other clinically established methods, it becomes possible to record and even quantify the extent of compensatory movements. In this way, an objective, user- and patient-friendly method is offered, which supports significantly physicians and therapists in their evaluation of OBPP.

show abstract

Accelerometer assessed upper limb activity in people with stroke: a validation study considering ambulatory and non-ambulatory activities

Cited by 8 publications

References 35 publications

Quantification of Movement in Stroke Patients under Free Living Conditions Using Wearable Sensors: A Systematic Review

Quantification of Movement in Stroke Patients under Free Living Conditions Using Wearable Sensors: A Systematic Review

Clinical research on neurological and psychiatric diagnosis and monitoring using wearable devices: A literature review

The use of accelerometers to assess upper limb function in patients with obstetric brachial plexus palsy

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