A Kinect-based system for cognitive rehabilitation exercises monitoring

González-Ortega, D.; Pernas, Francisco Javier Díaz; Martínez‐Zarzuela, Mario; Antón-Rodríguez, M.

doi:10.1016/j.cmpb.2013.10.014

Cited by 150 publications

(77 citation statements)

References 28 publications

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“…The Kinect is a visual-based tracking system that uses a single red green-blue camera and depth sensor to provide a full body, three-dimensional motion capture based on ana tomical landmarks and joint positions without markers or handheld controllers [26]. While the Kinect was origi nally designed for gaming, it is currently being used as a rehabilitation tool for intervention in stroke [26], cerebral palsy [27], cognitive dysfunction [28], and fall preven tion [29]. The Kinect is also being used for the assess ment of postural control [30], gait [31], balance [3], static foot posture [32], body sway [33], and common motor movements [34], all with promising comparisons to three-dimensional gold standard systems.…”

Section: Microsoft Kinectmentioning

confidence: 99%

Reliability and validity of the Microsoft Kinect for assessment of manual wheelchair propulsion

Milgrom¹,

OTD²,

Foreman³

et al. 2016

J Rehabil Res Dev

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Abstract-Concurrent validity and test-retest reliability of the Microsoft Kinect in quantification of manual wheelchair pro pulsion were examined. Data were collected from five manual wheelchair users on a roller system. Three Kinect sensors were used to assess test-retest reliability with a still pose. Three sys tems were used to assess concurrent validity of the Kinect to measure propulsion kinematics (joint angles, push loop charac teristics): Kinect, Motion Analysis, and Dartfish ProSuite (Dart fish joint angles were limited to shoulder and elbow flexion). Intraclass correlation coefficients (ICCs) revealed good reliabil ity (0.87-0.99) between five of the six joint angles (neck flexion, shoulder flexion, shoulder abduction, elbow flexion, wrist flexion). ICCs suggested good concurrent validity for elbow flexion between the Kinect and Dartfish and between the Kinect and Motion Analysis. Good concurrent validity was revealed for maximum height, hand-axle relationship, and maximum area (0.92-0.95) between the Kinect and Dartfish and maxi mum height and hand-axle relationship (0.89-0.96) between the Kinect and Motion Analysis. Analysis of variance revealed sig nificant differences (p < 0.05) in maximum length between Dartfish (mean 58.76 cm) and the Kinect (40.16 cm). Results pose promising research and clinical implications for propul sion assessment and overuse injury prevention with the applica tion of current findings to future technology.

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Section: Microsoft Kinectmentioning

confidence: 99%

Reliability and validity of the Microsoft Kinect for assessment of manual wheelchair propulsion

Milgrom¹,

OTD²,

Foreman³

et al. 2016

J Rehabil Res Dev

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“…Due to its availability Kinect has become very popular in the area of research, mainly in the field of robotics (Hernández-Lópeza et al, 2012) and human-computer interaction. Other sorts of utilization were proposed as well -Changa, Chenb & Huang (2011) and González-Ortega et al (2014) pointed out possibility of its usage for physical rehabilitation to be successful. A different -and for us more interesting -research is the one of Dominio, Donadeo & Zanuttigh (2013) which resulted in hand gestures recognition using the extracted depth data.…”

Section: Hand Tracking and Gesture Recognitionmentioning

confidence: 99%

Approach to Hand Tracking and Gesture Recognition Based on Depth-Sensing Cameras and EMG Monitoring

Kainz¹,

Jakab²

2014

AIP

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Abstract:In this paper, a new approach for hand tracking and gesture recognition based on the Leap Motion device and surface electromyography (SEMG) is presented. The system is about to process the depth image information and the electrical activity produced by skeletal muscles on forearm. The purpose of such combination is enhancement in the gesture recognition rate. As a first we analyse the conventional approaches toward hand tracking and gesture recognition and present the results of various researches. Successive topic gives brief overview of depth-sensing cameras with focus on Leap motion device where we test its accuracy of fingers recognition. The vision-SEMG-based system is to be potentially applicable to many areas of human computer interaction.

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“…Existe um amplo acervo de trabalhos na área médica como [Gallo, Placitelli e Ciampi 2011], [González-Ortega et al 2014] e [Ganesan e Anthony 2012], no qual o NuiMod também pode ser aplicado. Todos estes projetos foram criados para utilização em ambiente desktop e não permitem, de maneira geral, que os usuários modelem seus próprios gestos.…”

Section: Cenários Para Aplicaçãounclassified