Finger application using K-Curvature method and Kinect sensor in real-time

This chapter outlines the current state of the art of Kinect sensor gait and activity authentication. It also focuses on emotional cues that could be observed from human body and posture. It presents a prototype of a system that combines recently developed behavioral gait and posture recognition methods for human emotion identification. A backbone of the system is Kinect sensor gait recognition, which explores the relationship between joint-relative angles and joint-relative distances through machine learning. The chapter then introduces a real-time gesture recognition system developed using Kinect sensor and trained with SVM classifier. Preliminary experimental results demonstrate accuracy and feasibility of using such systems in real-world scenarios. While gait and emotion from body movement has been researched in the context of standalone biometric security systems, they were never previously explored for physiotherapy rehabilitation and real-time patient feedback. The survey of recent progress and open problems in crucial areas of medical patient rehabilitation and rescue operations conclude this chapter.

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Multi-Modal Motion-Capture-Based Biometric Systems for Emergency Response and Patient Rehabilitation

Research Anthology on Rehabilitation Practices and Therapy ◽

10.4018/978-1-7998-3432-8.ch032 ◽

2021 ◽

pp. 653-678

Author(s):

Marina L. Gavrilova ◽

Ferdous Ahmed ◽

A. S. M. Hossain Bari ◽

Ruixuan Liu ◽

Tiantian Liu ◽

...

Keyword(s):

Real Time ◽

Body Movement ◽

Gait Recognition ◽

Medical Patient ◽

Recognition System ◽

Svm Classifier ◽

Kinect Sensor ◽

Open Problems ◽

Emotion Identification ◽

Emotional Cues

This chapter outlines the current state of the art of Kinect sensor gait and activity authentication. It also focuses on emotional cues that could be observed from human body and posture. It presents a prototype of a system that combines recently developed behavioral gait and posture recognition methods for human emotion identification. A backbone of the system is Kinect sensor gait recognition, which explores the relationship between joint-relative angles and joint-relative distances through machine learning. The chapter then introduces a real-time gesture recognition system developed using Kinect sensor and trained with SVM classifier. Preliminary experimental results demonstrate accuracy and feasibility of using such systems in real-world scenarios. While gait and emotion from body movement has been researched in the context of standalone biometric security systems, they were never previously explored for physiotherapy rehabilitation and real-time patient feedback. The survey of recent progress and open problems in crucial areas of medical patient rehabilitation and rescue operations conclude this chapter.

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Real-Time Pose Estimation of a Mobile Rover Using Kinect Sensor

SSRN Electronic Journal ◽

10.2139/ssrn.3575469 ◽

2019 ◽

Author(s):

Mahesh K. Singh

Keyword(s):

Real Time ◽

Pose Estimation ◽

Kinect Sensor

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Real-time 3D reconstruction of the human torso using a Kinect sensor

Latin America Optics and Photonics Conference ◽

10.1364/laop.2014.lth4a.21 ◽

2014 ◽

Author(s):

J. F. Flórez ◽

C.R. Contreras ◽

J. E. Meneses

Keyword(s):

3D Reconstruction ◽

Real Time ◽

Kinect Sensor

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Development of a Kinect Rehabilitation System

International Journal of Online and Biomedical Engineering (iJOE) ◽

10.3991/ijoe.v9is8.3378 ◽

2013 ◽

Vol 9 (S8) ◽

pp. 38 ◽

Cited By ~ 3

Author(s):

João Couto Soares ◽

Ágata Vieira ◽

Octavian Postolache ◽

Joaquim Gabriel

Keyword(s):

Real Time ◽

Serious Games ◽

Microsoft Kinect ◽

Visual Environment ◽

Kinect Sensor ◽

Game Engine ◽

Kinect Camera ◽

Home Based ◽

Rehabilitation System

Abstractâ??Microsoft Kinect camera has been used in serious games applications, like for rehabilitation purposes, almost since it became available in the market. This article presents a clinical view regarding home-based physiotherapy for patients that suffered a stroke and details on the development of the rehabilitation system - Kinect-RehabPlay. This system uses the Kinect sensor together with the Unity3D game engine software to create the animation and visual environment. Currently, it is able to track, recording and comparing movements (doctor versus patient), and adjust the game configuration in real-time.

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