A Review on the Use of Microsoft Kinect for Gait Abnormality and Postural Disorder Assessment

Bawa, Anthony; Banitsas, Konstantinos; Abbod, Maysam F.

doi:10.1155/2021/4360122

Cited by 20 publications

(14 citation statements)

References 60 publications

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“…The studies focused specifically on measures to detect postural instability, shoulder position angulation and body joint angles, but the accuracy in the detection of posture disorders was not considered. 18 Another article evaluated the possibility to provide an accurate and automated assessment of axial postural abnormalities in PD patients by Kinect, evaluating the ICC between the angles calculated and the MDS‐UPDRS‐III 3.13 score. 19 These studies enrich the potential set of tools available for the early detection of axial postural abnormalities but do not consider the recent MDS consensus‐based criteria for their diagnosis.…”

Section: Discussionmentioning

confidence: 99%

“…A recent review reported 13 studies about postural disorder assessment with Microsoft Kinect, a motion‐sensing device for interaction with game consoles and computers. The studies focused specifically on measures to detect postural instability, shoulder position angulation and body joint angles, but the accuracy in the detection of posture disorders was not considered 18 . Another article evaluated the possibility to provide an accurate and automated assessment of axial postural abnormalities in PD patients by Kinect, evaluating the ICC between the angles calculated and the MDS‐UPDRS‐III 3.13 score 19 .…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Assessment of Axial Postural Abnormalities in Parkinsonism: Automatic Picture Analysis Software

Artusi

Geroin

Imbalzano

et al. 2023

Movement Disord Clin Pract

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Background Background: Software-based measurements of axial postural abnormalities in Parkinson's disease (PD) are the gold standard but may be time-consuming and not always feasible in clinical practice. An automatic and reliable software to accurately obtain real-time spine flexion angles according to the recently proposed consensus-based criteria would be a useful tool for both research and clinical practice. Objective Objective: We aimed to develop and validate a new software based on Deep Neural Networks to perform automatic measures of PD axial postural abnormalities. Methods Methods: A total of 76 pictures from 55 PD patients with different degrees of anterior and lateral trunk flexion were used for the development and pilot validation of a new software called AutoPosturePD (APP); postural abnormalities were measured in lateral and posterior view using the freeware NeuroPostureApp (gold standard) and compared with the automatic measurement provided by the APP. Sensitivity and specificity for the diagnosis of camptocormia and Pisa syndrome were assessed. ResultsResults: We found an excellent agreement between the new APP and the gold standard for lateral trunk flexion (intraclass correlation coefficient [ICC] 0.960, IC95% 0.913-0.982, P < 0.001), anterior trunk flexion with thoracic fulcrum (ICC 0.929, IC95% 0.846-0.968, P < 0.001) and anterior trunk flexion with lumbar fulcrum (ICC 0.991, IC95% 0.962-0.997, P < 0.001). Sensitivity and specificity were 100% and 100% for detecting Pisa syndrome, 100% and 95.5% for camptocormia with thoracic fulcrum, 100% and 80.9% for camptocormia with lumbar fulcrum. Conclusions Conclusions: AutoPosturePD is a valid tool for spine flexion measurement in PD, accurately supporting the diagnosis of Pisa syndrome and camptocormia.Axial postural abnormalities, including excessive forward and lateral trunk flexion, are common motor symptoms in Parkinson's disease (PD) and atypical parkinsonism. 1,2 These symptoms, largely resistant to dopaminergic therapy in PD patients, proved to be associated with higher motor dysfunction, falls, autonomy loss, and reduced quality of life. 1,2 The lack of a common classification and measurement methods for these symptoms led to uncertainty in their epidemiology, pathophysiological features, and therapeutic approaches. [1][2][3][4] Recently, axial postural abnormalities have been classified by the International Movement Disorders Society (MDS) Task Force on Postural Abnormalities in Parkinsonism in different types, according with diagnostic cut-offs (ie, angles and fulcra) of spine flexion based on patients' pictures captured in standing position, both in frontal and sagittal plane. 5 In this consensus, the authors used a free software-based measurement tool (Neu-roPostureApp -

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Assessment of Axial Postural Abnormalities in Parkinsonism: Automatic Picture Analysis Software

Artusi

Geroin

Imbalzano

et al. 2023

Movement Disord Clin Pract

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“…The technological application of markerless motion capture during the gait analysis supports the validation in calculating body proportions (angles between body parts), timing, direction, and velocity without attaching markers to the skin. The main items of observation are; Posture, movement initiation and movement sequencing [46][47][48][49].…”

Section: Quality Of Lifementioning

confidence: 99%

Muva physical activity intervention to improve social functioning in people with a severe mental illness: study protocol of a pragmatic stepped wedge cluster randomized trial

et al. 2022

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Background People with severe mental illness (SMI) often suffer from long-lasting symptoms that negatively influence their social functioning, their ability to live a meaningful life, and participation in society. Interventions aimed at increasing physical activity can improve social functioning, but people with SMI experience multiple barriers to becoming physically active. Besides, the implementation of physical activity interventions in day-to-day practice is difficult. In this study, we aim to evaluate the effectiveness and implementation of a physical activity intervention to improve social functioning, mental and physical health. Methods In this pragmatic stepped wedge cluster randomized controlled trial we aim to include 100 people with SMI and their mental health workers from a supported housing organization. The intervention focuses on increasing physical activity by implementing group sports activities, active guidance meetings, and a serious game to set physical activity goals. We aim to decrease barriers to physical activity through active involvement of the mental health workers, lifestyle courses, and a medication review. Participating locations will be divided into four clusters and randomization will decide the start of the intervention. The primary outcome is social functioning. Secondary outcomes are quality of life, symptom severity, physical activity, cardiometabolic risk factors, cardiorespiratory fitness, and movement disturbances with specific attention to postural adjustment and movement sequencing in gait. In addition, we will assess the implementation by conducting semi-structured interviews with location managers and mental health workers and analyze them by direct content analysis. Discussion This trial is innovative since it aims to improve social functioning in people with SMI through a physical activity intervention which aims to lower barriers to becoming physically active in a real-life setting. The strength of this trial is that we will also evaluate the implementation of the intervention. Limitations of this study are the risk of poor implementation of the intervention, and bias due to the inclusion of a medication review in the intervention that might impact outcomes. Trial registration This trial was registered prospectively in The Netherlands Trial Register (NTR) as NTR NL9163 on December 20, 2020. As the The Netherlands Trial Register is no longer available, the trial can now be found in the International Clinical Trial Registry Platform via: https://trialsearch.who.int/Trial2.aspx?TrialID=NL9163.

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“…[6][7][8] The common commercially available sensors used for markerless motion analysis are Leap Motion Controller (LMC; Leap Motion Inc., San Francisco, USA) and consecutive versions of Microsoft Kinect sensors (Kinect for Windows v. 1 (V1) and Kinect for Windows v. 2 (V2); Microsoft Corp., Redmond, USA). 9,10 For center-based and home rehabilitation purposes, Nintendo Wii Mote, Wii Balance Board (Nintendo Inc., Redmond, USA) and Microsoft Kinect motion-sensing game controllers have gained popularity over the past years. [11][12][13][14] Since Microsoft had released Azure Kinect Developer Kit (DK) in 2019, only a few studies were published concerning its usage.…”

Section: Introductionmentioning

confidence: 99%

Wrist motion assessment using Microsoft Azure Kinect DK: A reliability study in healthy individuals

Królikowska¹,

Maj²,

Dejnek³

et al. 2022

Adv Clin Exp Med

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Background. Motion analysis systems have been widely used in orthopedics and rehabilitation for diagnostics, patient monitoring and outcome evaluation purposes. Since Microsoft Azure Kinect Developer Kit (DK) had been released, only a few studies were published concerning its usage. However, it has not been used for wrist motion assessments, even though the use of standardized examinations with known reliability, validity and responsiveness remains a constant challenge.Objectives. This study aimed to examine the reliability of hand and forearm range of motion (ROM) measurements recorded using new software utilizing the Microsoft Azure Kinect DK. Materials and methods.Twenty-eight healthy males and 28 healthy females participated in measurements of active ROM for wrist extension, wrist flexion, radial deviation, ulnar deviation, and forearm supination and pronation on 3 separate occasions. Sessions 1 and 2 were carried out on the same day with a 90-minute rest period between each session, while the 3 rd session was conducted a week later. Data were recorded simultaneously in both limbs using a custom-made software developed by a software development company (Oleksy Medical & Sports Sciences, Łańcut, Poland) for the purposes of the present study using Microsoft Azure Kinect DK. The assessment of intra-day and inter-day reliability was based on intraclass correlation coefficient (ICC) calculations and interpreted based on commonly used guidelines.Results. In the group of males, the lowest ICC was 0.846 for intra-day comparisons and 0.816 for inter-day analyses. In the female group, the lowest ICC for intra-day comparisons was 0.826 and exceeded 0.833 for inter-day comparisons.Conclusions. The developed software using Microsoft Azure Kinect DK demonstrated high reliability in measuring wrist and forearm active ROM. These promising results support the use of Microsoft Azure Kinect DK in a clinical capacity as a potential hand assessment and rehabilitation tool.

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A Review on the Use of Microsoft Kinect for Gait Abnormality and Postural Disorder Assessment

Cited by 20 publications

References 60 publications

Assessment of Axial Postural Abnormalities in Parkinsonism: Automatic Picture Analysis Software

Assessment of Axial Postural Abnormalities in Parkinsonism: Automatic Picture Analysis Software

Muva physical activity intervention to improve social functioning in people with a severe mental illness: study protocol of a pragmatic stepped wedge cluster randomized trial

Wrist motion assessment using Microsoft Azure Kinect DK: A reliability study in healthy individuals

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