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Poitras I, Gagné-Pelletier L, Clouâtre J, Flamand VH, Campeau-Lecours A, Mercier C. Optimizing Epoch Length and Activity Count Threshold Parameters in Accelerometry: Enhancing Upper Extremity Use Quantification in Cerebral Palsy. SENSORS (BASEL, SWITZERLAND) 2024; 24:1100. [PMID: 38400258 PMCID: PMC10892357 DOI: 10.3390/s24041100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 01/29/2024] [Accepted: 02/06/2024] [Indexed: 02/25/2024]
Abstract
Various accelerometry protocols have been used to quantify upper extremity (UE) activity, encompassing diverse epoch lengths and thresholding methods. However, there is no consensus on the most effective approach. The aim of this study was to delineate the optimal parameters for analyzing accelerometry data to quantify UE use in individuals with unilateral cerebral palsy (CP). METHODS A group of adults with CP (n = 15) participated in six activities of daily living, while a group of children with CP (n = 14) underwent the Assisting Hand Assessment. Both groups performed the activities while wearing ActiGraph GT9X-BT devices on each wrist, with concurrent video recording. Use ratio (UR) derived from accelerometry and video analysis and accelerometer data were compared for different epoch lengths (1, 1.5, and 2 s) and activity count (AC) thresholds (between 2 and 150). RESULTS In adults, results are comparable across epoch lengths, with the best AC thresholds being ≥ 100. In children, results are similar across epoch lengths of 1 and 1.5 (optimal AC threshold = 50), while the optimal threshold is higher with an epoch length of 2 (AC = 75). CONCLUSIONS The combination of epoch length and AC thresholds should be chosen carefully as both influence the validity of the quantification of UE use.
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Affiliation(s)
- Isabelle Poitras
- Centre for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre Intégré Universitaire de Santé et Services Sociaux de la Capitale-Nationale, Quebec City, QC G1M 2S8, Canada; (I.P.); (L.G.-P.); (J.C.); (V.H.F.); (A.C.-L.)
- School of Rehabilitation Sciences, Laval University, Quebec City, QC G1V 0A6, Canada
| | - Léandre Gagné-Pelletier
- Centre for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre Intégré Universitaire de Santé et Services Sociaux de la Capitale-Nationale, Quebec City, QC G1M 2S8, Canada; (I.P.); (L.G.-P.); (J.C.); (V.H.F.); (A.C.-L.)
- School of Rehabilitation Sciences, Laval University, Quebec City, QC G1V 0A6, Canada
| | - Jade Clouâtre
- Centre for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre Intégré Universitaire de Santé et Services Sociaux de la Capitale-Nationale, Quebec City, QC G1M 2S8, Canada; (I.P.); (L.G.-P.); (J.C.); (V.H.F.); (A.C.-L.)
- Department of Mechanical Engineering, Laval University, Quebec City, QC G1V 0A6, Canada
| | - Véronique H. Flamand
- Centre for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre Intégré Universitaire de Santé et Services Sociaux de la Capitale-Nationale, Quebec City, QC G1M 2S8, Canada; (I.P.); (L.G.-P.); (J.C.); (V.H.F.); (A.C.-L.)
- School of Rehabilitation Sciences, Laval University, Quebec City, QC G1V 0A6, Canada
| | - Alexandre Campeau-Lecours
- Centre for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre Intégré Universitaire de Santé et Services Sociaux de la Capitale-Nationale, Quebec City, QC G1M 2S8, Canada; (I.P.); (L.G.-P.); (J.C.); (V.H.F.); (A.C.-L.)
- Department of Mechanical Engineering, Laval University, Quebec City, QC G1V 0A6, Canada
| | - Catherine Mercier
- Centre for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre Intégré Universitaire de Santé et Services Sociaux de la Capitale-Nationale, Quebec City, QC G1M 2S8, Canada; (I.P.); (L.G.-P.); (J.C.); (V.H.F.); (A.C.-L.)
- School of Rehabilitation Sciences, Laval University, Quebec City, QC G1V 0A6, Canada
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Bhat SG, Shin AY, Kaufman KR. Upper extremity asymmetry due to nerve injuries or central neurologic conditions: a scoping review. J Neuroeng Rehabil 2023; 20:151. [PMID: 37940959 PMCID: PMC10634143 DOI: 10.1186/s12984-023-01277-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 11/01/2023] [Indexed: 11/10/2023] Open
Abstract
BACKGROUND Peripheral nerve injuries and central neurologic conditions can result in extensive disabilities. In cases with unilateral impairment, assessing the asymmetry between the upper extremity has been used to assess outcomes of treatment and severity of injury. A wide variety of validated and novel tests and sensors have been utilized to determine the upper extremity asymmetry. The purpose of this article is to review the literature and define the current state of the art for describing upper extremity asymmetry in patients with peripheral nerve injuries or central neurologic conditions. METHOD An electronic literature search of PubMed, Scopus, Web of Science, OVID was performed for publications between 2000 to 2022. Eligibility criteria were subjects with neurological conditions/injuries who were analyzed for dissimilarities in use between the upper extremities. Data related to study population, target condition/injury, types of tests performed, sensors used, real-world data collection, outcome measures of interest, and results of the study were extracted. Sackett's Level of Evidence was used to judge the quality of the articles. RESULTS Of the 7281 unique articles, 112 articles met the inclusion criteria for the review. Eight target conditions/injuries were identified (Brachial Plexus Injury, Cerebral Palsy, Multiple Sclerosis, Parkinson's Disease, Peripheral Nerve Injury, Spinal Cord Injury, Schizophrenia, and stroke). The tests performed were classified into thirteen categories based on the nature of the test and data collected. The general results related to upper extremity asymmetry were listed for all the reviewed articles. Stroke was the most studied condition, followed by cerebral palsy, with kinematics and strength measurement tests being the most frequently used tests. Studies with a level of evidence level II and III increased between 2000 and 2021. The use of real-world evidence-based data, and objective data collection tests also increased in the same period. CONCLUSION Adequately powered randomized controlled trials should be used to study upper extremity asymmetry. Neurological conditions other than stroke should be studied further. Upper extremity asymmetry should be measured using objective outcome measures like motion tracking and activity monitoring in the patient's daily living environment.
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Affiliation(s)
- Sandesh G Bhat
- Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, 55905, USA
| | - Alexander Y Shin
- Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, 55905, USA
| | - Kenton R Kaufman
- Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, 55905, USA.
- Motion Analysis Laboratory, Mayo Clinic, DAHLC 4-214A, 200 First Street SW, Rochester, MN, 55905, USA.
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Li S, Gonzalez-Buonomo J, Ghuman J, Huang X, Malik A, Yozbatiran N, Magat E, Francisco GE, Wu H, Frontera WR. Aging after stroke: how to define post-stroke sarcopenia and what are its risk factors? Eur J Phys Rehabil Med 2022; 58:683-692. [PMID: 36062331 PMCID: PMC10022455 DOI: 10.23736/s1973-9087.22.07514-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 08/08/2022] [Accepted: 08/31/2022] [Indexed: 11/08/2022]
Abstract
BACKGROUND Sarcopenia, generally described as "aging-related loss of skeletal muscle mass and function", can occur secondary to a systemic disease. AIM This project aimed to study the prevalence of sarcopenia in chronic ambulatory stroke survivors and its associated risk factors using the two most recent diagnostic criteria. DESIGN A cross-sectional observational study. SETTING A scientific laboratory. POPULATION Chronic stroke. METHODS Twenty-eight ambulatory chronic stroke survivors (12 females; mean age=57.8±11.8 years; time after stroke=76±45 months), hand-grip strength, gait speed, and appendicular skeletal muscle mass (ASM) were measured to define sarcopenia. Risk factors, including motor impairment and spasticity, were identified using regression analysis. RESULTS The prevalence of sarcopenia varied between 18% and 25% depending on the diagnostic criteria used. A significant difference was seen in the prevalence of low hand grip strength on the affected side (96%) when compared to the contralateral side (25%). The prevalence of slow gait speed was 86% while low ASM was present in 89% of the subjects. Low ASM was marginally negatively correlated with time since stroke and gait speed, but no correlation was observed with age, motor impairment, or spasticity. ASM loss, bone loss and fat deposition were significantly greater in the affected upper limb than in the affected lower limb. Regression analyses showed that time since stroke was a factor associated with bone and muscle loss in the affected upper limb, spasticity had a protective role for muscle loss in the affected lower limb, and walking had a protective role for bone loss in the lower limb. CONCLUSIONS The prevalence of sarcopenia in stroke survivors is high and is a multifactorial process that is not age-related. Different risk factors contribute to muscle loss in the upper and lower limbs after stroke. CLINICAL REHABILITATION IMPACT Clinicians need to be aware of high prevalence of sarcopenia in chronic stroke survivors. Sarcopenia is more evident in the upper than lower limbs. Clinicians also need to understand potential protective roles of some factors, such as spasticity and walking for the muscles in the lower limb.
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Affiliation(s)
- Sheng Li
- Department of Physical Medicine and Rehabilitation, McGovern Medical School, University of Texas Health Science Center, Houston, TX, USA -
- NeuroRecovery Research Center, TIRR Memorial Hermann Hospital, Houston, TX, USA -
| | | | | | - Xinran Huang
- Department of Biostatistics and Data Science, University of Texas Health Science Center, Houston, TX, USA
| | - Aila Malik
- Department of Physical Medicine and Rehabilitation, McGovern Medical School, University of Texas Health Science Center, Houston, TX, USA
- NeuroRecovery Research Center, TIRR Memorial Hermann Hospital, Houston, TX, USA
| | - Nuray Yozbatiran
- Department of Physical Medicine and Rehabilitation, McGovern Medical School, University of Texas Health Science Center, Houston, TX, USA
- NeuroRecovery Research Center, TIRR Memorial Hermann Hospital, Houston, TX, USA
| | - Elaine Magat
- Department of Physical Medicine and Rehabilitation, McGovern Medical School, University of Texas Health Science Center, Houston, TX, USA
- NeuroRecovery Research Center, TIRR Memorial Hermann Hospital, Houston, TX, USA
| | - Gerard E Francisco
- Department of Physical Medicine and Rehabilitation, McGovern Medical School, University of Texas Health Science Center, Houston, TX, USA
- NeuroRecovery Research Center, TIRR Memorial Hermann Hospital, Houston, TX, USA
| | - Hulin Wu
- Department of Biostatistics and Data Science, University of Texas Health Science Center, Houston, TX, USA
| | - Walter R Frontera
- Department of Physical Medicine, Rehabilitation, and Sports Medicine, University of Puerto Rico School of Medicine, San Juan, Puerto Rico
- Department of Physiology, University of Puerto Rico School of Medicine, San Juan, Puerto Rico
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Bernaldo de Quirós M, Douma E, van den Akker-Scheek I, Lamoth CJC, Maurits NM. Quantification of Movement in Stroke Patients under Free Living Conditions Using Wearable Sensors: A Systematic Review. SENSORS (BASEL, SWITZERLAND) 2022; 22:1050. [PMID: 35161796 PMCID: PMC8840016 DOI: 10.3390/s22031050] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 01/19/2022] [Accepted: 01/25/2022] [Indexed: 05/06/2023]
Abstract
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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Affiliation(s)
- Mariano Bernaldo de Quirós
- Department of Neurology, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands;
| | - E.H. Douma
- Department of Human Movement Sciences, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands; (E.H.D.); (C.J.C.L.)
| | - Inge van den Akker-Scheek
- Department of Orthopedics, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands;
| | - Claudine J. C. Lamoth
- Department of Human Movement Sciences, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands; (E.H.D.); (C.J.C.L.)
| | - Natasha M. Maurits
- Department of Neurology, University Medical Center Groningen, University of Groningen, 9700 RB Groningen, The Netherlands;
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