scholarly journals Recognition of postures and Freezing of Gait in Parkinson's disease patients using Microsoft Kinect sensor

2015 ◽  
Author(s):  
A. Amini Maghsoud Bigy ◽  
K. Banitsas ◽  
A. Badii ◽  
J. Cosmas
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Freezing Of Gait ◽  
Microsoft Kinect ◽  
Kinect Sensor ◽  
Microsoft Kinect Sensor

scholarly journals Exploring Movement Impairments in Patients With Parkinson's Disease Using the Microsoft Kinect Sensor: A Feasibility Study

2021 ◽  
Vol 11 ◽  
Author(s):  
Ditte Rudå ◽  
Gudmundur Einarsson ◽  
Anne Sofie Schott Andersen ◽  
Jannik Boll Matthiassen ◽  
Christoph U. Correll ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Motor Performance ◽  
Rating Scales ◽  
Rating Scale ◽  
Motor Task ◽  
Microsoft Kinect ◽  
Healthy Controls ◽  
Kinect Sensor ◽  
Microsoft Kinect Sensor

Background: Current assessments of motor symptoms in Parkinson's disease are often limited to clinical rating scales.Objectives: To develop a computer application using the Microsoft Kinect sensor to assess performance-related bradykinesia.Methods: The developed application (Motorgame) was tested in patients with Parkinson's disease and healthy controls. Participants were assessed with the Movement Disorder Society Unified Parkinson's disease Rating Scale (MDS-UPDRS) and standardized clinical side effect rating scales, i.e., UKU Side Effect Rating Scale and Simpson-Angus Scale. Additionally, tests of information processing (Symbol Coding Task) and motor speed (Token Motor Task), together with a questionnaire, were applied.Results: Thirty patients with Parkinson's disease and 33 healthy controls were assessed. In the patient group, there was a statistically significant (p < 0.05) association between prolonged time of motor performance in the Motorgame and upper body rigidity and bradykinesia (MDS-UPDRS) with the strongest effects in the right hand (p < 0.001). In the entire group, prolonged time of motor performance was significantly associated with higher Simson-Angus scale rigidity score and higher UKU hypokinesia scores (p < 0.05). A shortened time of motor performance was significantly associated with higher scores on information processing (p < 0.05). Time of motor performance was not significantly associated with Token Motor Task, duration of illness, or hours of daily physical activity. The Motorgame was well-accepted.Conclusions: In the present feasibility study the Motorgame was able to detect common motor symptoms in Parkinson's disease in a statistically significant and clinically meaningful way, making it applicable for further testing in larger samples.

scholarly journals Accuracy of the Microsoft Kinect sensor for measuring movement in people with Parkinson's disease

2014 ◽  
Vol 39 (4) ◽  
pp. 1062-1068 ◽  
Author(s):  
Brook Galna ◽  
Gillian Barry ◽  
Dan Jackson ◽  
Dadirayi Mhiripiri ◽  
Patrick Olivier ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Microsoft Kinect ◽  
Kinect Sensor ◽  
Microsoft Kinect Sensor

scholarly journals Kin-FOG: Automatic Simulated Freezing of Gait (FOG) Assessment System for Parkinson’s Disease

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2416 ◽  
Author(s):  
Sara Soltaninejad ◽  
Irene Cheng ◽  
Anup Basu
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Freezing Of Gait ◽  
The Elderly ◽  
Assessment System ◽  
Microsoft Kinect ◽  
Data Sets ◽  
Fog Prediction ◽  
Foot Joint ◽  
Rehabilitation Clinic

Parkinson’s disease (PD) is one of the leading neurological disorders in the world with an increasing incidence rate for the elderly. Freezing of Gait (FOG) is one of the most incapacitating symptoms for PD especially in the later stages of the disease. FOG is a short absence or reduction of ability to walk for PD patients which can cause fall, reduction in patients’ quality of life, and even death. Existing FOG assessments by doctors are based on a patient’s diaries and experts’ manual video analysis which give subjective, inaccurate, and unreliable results. In the present research, an automatic FOG assessment system is designed for PD patients to provide objective information to neurologists about the FOG condition and the symptom’s characteristics. The proposed FOG assessment system uses an RGB-D sensor based on Microsoft Kinect V2 for capturing data for 5 healthy subjects who are trained to imitate the FOG phenomenon. The proposed FOG assessment system is called “Kin-FOG”. The analysis of foot joint trajectory of the motion captured by Kinect is used to find the FOG episodes. The evaluation of Kin-FOG is performed by two types of experiments, including: (1) simple walking (SW); and (2) walking with turning (WWT). Since the standing mode has features similar to a FOG episode, our Kin-FOG system proposes a method to distinguish between the FOG and standing episodes. Therefore, two general groups of experiments are conducted with standing state (WST) and without standing state (WOST). The gradient displacement of the angle between the foot and the ground is used as the feature for discriminating between FOG and standing modes. These experiments are conducted with different numbers of FOGs for getting reliable and general results. The Kin-FOG system reports the number of FOGs, their lengths, and the time slots when they occur. Experimental results demonstrate Kin-FOG has around 90% accuracy rate for FOG prediction in both experiments for different tasks (SW, WWT). The proposed Kin-FOG system can be used as a remote application at a patient’s home or a rehabilitation clinic for sending a neurologist the required FOG information. The reliability and generality of the proposed system will be evaluated for bigger data sets of actual PD subjects.

Chronological View of Peak and Diphasic Dyskinesia, Wearing Off and Freezing of Gait in Parkinson’s Disease

2019 ◽  
Vol 9 (4) ◽  
pp. 741-747 ◽  
Author(s):  
Young Eun Kim ◽  
Beomseok Jeon ◽  
Ji Young Yun ◽  
Hui-Jun Yang ◽  
Han-Joon Kim
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Freezing Of Gait ◽  
Wearing Off

Effects of music-based movement therapy on motor function, balance, gait, mental health, and quality of life for patients with Parkinson’s disease: A systematic review and meta-analysis

2021 ◽  
pp. 026921552199052
Author(s):  
Zonglei Zhou ◽  
Ruzhen Zhou ◽  
Wen Wei ◽  
Rongsheng Luan ◽  
Kunpeng Li
Keyword(s):  
Quality Of Life ◽  
Mental Health ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Motor Function ◽  
Meta Analysis ◽  
Freezing Of Gait ◽  
Movement Therapy ◽  
Walking Velocity

Objective: To conduct a systematic review evaluating the effects of music-based movement therapy on motor function, balance, gait, mental health, and quality of life among individuals with Parkinson’s disease. Data sources: A systematic search of PubMed, Embase, Cochrane Library, Web of Science, PsycINFO, CINAHL, and Physiotherapy Evidence Database was carried out to identify eligible papers published up to December 10, 2020. Review methods: Literature selection, data extraction, and methodological quality assessment were independently performed by two investigators. Publication bias was determined by funnel plot and Egger’s regression test. “Trim and fill” analysis was performed to adjust any potential publication bias. Results: Seventeen studies involving 598 participants were included in this meta-analysis. Music-based movement therapy significantly improved motor function (Unified Parkinson’s Disease Rating Scale motor subscale, MD = −5.44, P = 0.002; Timed Up and Go Test, MD = −1.02, P = 0.001), balance (Berg Balance Scale, MD = 2.02, P < 0.001; Mini-Balance Evaluation Systems Test, MD = 2.95, P = 0.001), freezing of gait (MD = −2.35, P = 0.039), walking velocity (MD = 0.18, P < 0.001), and mental health (SMD = −0.38, P = 0.003). However, no significant effects were observed on gait cadence, stride length, and quality of life. Conclusion: The findings of this study show that music-based movement therapy is an effective treatment approach for improving motor function, balance, freezing of gait, walking velocity, and mental health for patients with Parkinson’s disease.

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