Bayesian classification and analysis of gait disorders using image and depth sensors of Microsoft Kinect

Procházka, Aleš; Vyšata, Oldřich; Vališ, Martin; Ťupa, Ondřej; Schätz, Martin; Mařı́k, Vladimı́r

doi:10.1016/j.dsp.2015.05.011

Cited by 93 publications

(62 citation statements)

References 48 publications

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“…Inertial sensors are also extensively used for ADL analysis, balance assessment and gait analysis of older people . The use of a Kinect sensor in gait analysis has gained attention of researchers for gait pattern recognition and classification [24,25].…”

Section: Quantitative Assessmentmentioning

confidence: 99%

Assessment of frailty: a survey of quantitative and clinical methods

Panhwar

Naghdy

et al. 2019

BMC biomed eng

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Background: Frailty assessment is a critical approach in assessing the health status of older people. The clinical tools deployed by geriatricians to assess frailty can be grouped into two categories; using a questionnaire-based method or analyzing the physical performance of the subject. In performance analysis, the time taken by a subject to complete a physical task such as walking over a specific distance, typically three meters, is measured. The questionnaire-based method is subjective, and the time-based performance analysis does not necessarily identify the kinematic characteristics of motion and their root causes. However, kinematic characteristics are crucial in measuring the degree of frailty. Results: The studies reviewed in this paper indicate that the quantitative analysis of activity of daily living, balance and gait are significant methods for assessing frailty in older people. Kinematic parameters (such as gait speed) and sensor-derived parameters are also strong markers of frailty. Seventeen gait parameters are found to be sensitive for discriminating various frailty levels. Gait velocity is the most significant parameter. Short term monitoring of daily activities is a more significant method for frailty assessment than is long term monitoring and can be implemented easily using clinical tests such as sit to stand or stand to sit. The risk of fall can be considered an outcome of frailty. Conclusion: Frailty is a multi-dimensional phenomenon that is defined by various domains; physical, social, psychological and environmental. The physical domain has proven to be essential in the objective determination of the degree of frailty in older people. The deployment of inertial sensor in clinical tests is an effective method for the objective assessment of frailty.

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Section: Quantitative Assessmentmentioning

confidence: 99%

Assessment of frailty: a survey of quantitative and clinical methods

Panhwar

Naghdy

et al. 2019

BMC biomed eng

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“…Another study proposed a method of Bayesian gait recognition using Microsoft (MS) Kinect image and depth sensors and skeleton tracking in three-dimensional space. The results included the estimation of the characteristics of selected gait features for patients with Parkinson's disease and for individuals from the reference sets, presentation of decision boundaries, and comparison of classification efficiency for different features [19]. Synnot et al [20] proposed WiiPD, a game based approach to home-based objective assessment of Parkinson's disease that uses the Nintendo Wii Remote in combination with a number of bespoke data gathering methods providing an engaging and capturing a wide range of motor and non-motor metrics.…”

Section: Introductionmentioning

confidence: 99%

Motion analysis of Parkinson diseased patients using a video game approach

Grammatikopoulou

Dimitropoulos

Bostantjopoulou

et al. 2019

Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments

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Parkinson's disease (PD) is a progressive neurological disorder and the second most common age-related neurodegenerative disease after Alzheimer's disease. The primary symptoms of the disease are associated with the loss of motor skills affecting patients' movement and coordination and disrupting their daily life. Unfortunately, such motor symptoms cannot be fully relieved by therapeutic options. On the other hand, studies have shown that regular training and exercising can prove neuroprotective in PD patients helping them maintain independent longer. Based on recent studies stating that computer-based physical therapy games can be used as an option for facilitating PD rehabilitation exercise programs, we present the development of a body motion based videogame, using the Kinect sensor, targeted for PD patients. We tested twelve patients with advanced forms of PD motor symptoms (UPDRS motor score>20) and six initial stage PD patients (UPDRS motor score<20). All participants underwent an (UPDRS) motor skills pretest and afterwards performed three training sessions. In this paper, we will present part of our research aiming to analyze the movement patterns of PD patients in order to detect statistical significant differences between groups of different impairment level based on their UPDRS motor score and their performance. Consequently, we adopt a deep learning approach by analyzing the recorded human skeleton sequences for predicting the players' level of motor skills decline. Such methods and data can serve as preliminary evidence for further larger and controlled studies to propose such an exergame that can independently detect and adapt its difficulty level to better match players' ability providing a more targeted and personalized rehabilitation option.

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“…Video images have been used in [57] [92]. Microsoft (MS) Kinect image and depth sensors provide a simple 3D modeling using image and depth sensors which have shown to be effective in analysis of gait disorders [93] and to recognise PD gait [94].…”

Section: A Platforms For Validationmentioning

confidence: 99%

A Review on Accelerometry-Based Gait Analysis and Emerging Clinical Applications

Jarchi

Pope

Lee

et al. 2018

IEEE Rev. Biomed. Eng.

170

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Gait analysis continues to be an important technique for many clinical applications to diagnose and monitor certain diseases. Many mental and physical abnormalities cause measurable differences in a person's gait. Gait analysis has applications in sport, computer games, physical rehabilitation, clinical assessment, surveillance, human recognition, modeling, and many other fields. There are established methods using various sensors for gait analysis, of which accelerometers are one of the most often employed. Accelerometer sensors are generally more user friendly and less invasive. In this paper, we review research regarding accelerometer sensors used for gait analysis with particular focus on clinical applications. We provide a brief introduction to accelerometer theory followed by other popular sensing technologies. Commonly used gait phases and parameters are enumerated. The details of selecting the papers for review are provided. We also review several gait analysis software. Then we provide an extensive report of accelerometry-based gait analysis systems and applications, with additional emphasis on trunk accelerometry. We conclude this review with future research directions.

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Bayesian classification and analysis of gait disorders using image and depth sensors of Microsoft Kinect

Cited by 93 publications

References 48 publications

Assessment of frailty: a survey of quantitative and clinical methods

Assessment of frailty: a survey of quantitative and clinical methods

Motion analysis of Parkinson diseased patients using a video game approach

A Review on Accelerometry-Based Gait Analysis and Emerging Clinical Applications

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