Telehealth Using PoseNet-Based System for In-Home Rehabilitation

Chua, Jiaming; Ong, Lee Yeng; Leow, Meng-Chew

doi:10.3390/fi13070173

Cited by 23 publications

(14 citation statements)

References 29 publications

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“…Adding the number of joints analyzed is also a potential area for further research. Despite the low accuracy, the proposed method has the advantage of being easy in the data acquisition process because it does not require a sensor attached to the subject's body [21]. This method has the potential to be applied to in-home rehabilitation for the elderly.…”

Section: Classification Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Empirical Mode Decomposition and Hilbert Spectrum for Abnormality Detection in Normal and Abnormal Walking Transitions

Erfianto

Rizal

Hadiyoso

2023

IJERPH

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Sensor-based human activity recognition (HAR) is a method for observing a person’s activity in an environment. With this method, it is possible to monitor remotely. HAR can analyze a person’s gait, whether normal or abnormal. Some of its applications may use several sensors mounted on the body, but this method tends to be complex and inconvenient. One alternative to wearable sensors is using video. One of the most commonly used HAR platforms is PoseNET. PoseNET is a sophisticated platform that can detect the skeleton and joints of the body, which are then known as joints. However, a method is still needed to process the raw data from PoseNET to detect subject activity. Therefore, this research proposes a way to detect abnormalities in gait using empirical mode decomposition and the Hilbert spectrum and transforming keys-joints, and skeletons from vision-based pose detection into the angular displacement of walking gait patterns (signals). Joint change information is extracted using the Hilbert Huang Transform to study how the subject behaves in the turning position. Furthermore, it is determined whether the transition goes from normal to abnormal subjects by calculating the energy in the time-frequency domain signal. The test results show that during the transition period, the energy of the gait signal tends to be higher than during the walking period.

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Section: Classification Resultsmentioning

confidence: 99%

“…The deep sensor commonly used is the Microsoft Kinect, which can extract the skeleton from images [20]. RGB cameras usually require more intensive image processing methods such as PoseNet [9,21]. Meanwhile, for infrared, you can use infrared break beam sensors, ultrasonic sensors, and passive infrared sensors [19].…”

mentioning

confidence: 99%

Empirical Mode Decomposition and Hilbert Spectrum for Abnormality Detection in Normal and Abnormal Walking Transitions

Erfianto

Rizal

Hadiyoso

2023

IJERPH

View full text Add to dashboard Cite

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“…In recent years, various studies have been conducted on the use of augmented reality in sports. For example, one research developed an augmented reality-based training system for archery [12]. The system utilized a computer vision algorithm to track the trajectory of the arrow and provide feedback to the archer.…”

Section: Related Workmentioning

confidence: 99%

Development of Computer Vision-enabled Augmented Reality Games to Increase Motivation for Sports

Doskarayev¹,

Omarov²,

Omarov³

et al. 2023

IJACSA

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This research paper presents the development of computer vision-enabled augmented reality games based on action detection to increase motivation for sports. With the increasing popularity of digital games, physical activity and sports participation have been declining, especially among the younger generation. To address this issue, we developed a series of augmented reality games that require players to perform physical actions to progress and succeed in the game. These games were developed using computer vision technology to detect the players' movements and provide real-time feedback, enhancing the gaming experience and promoting physical activity. The results of our user study showed that participants who played the augmented reality games reported higher levels of motivation to engage in physical activity and sports. The findings suggest that computer vision-enabled augmented reality games can be an effective tool to promote physical activity and sports participation, especially among younger generations.

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“…Studies [6,16] show how OpenPose and similar camera-based systems could be used in telerehabilitation, but they are not dealing with the practical telerehabilitation applicability. Studies that evaluate the accuracy of motion detection typically study only one specific type of exercise motion.…”

Section: Related Workmentioning

confidence: 99%

Single Camera-Based Remote Physical Therapy: Verification on a Large Video Dataset

et al. 2022

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In recent years, several systems have been developed to capture human motion in real-time using common RGB cameras. This approach has great potential to become widespread among the general public as it allows the remote evaluation of exercise at no additional cost. The concept of using these systems in rehabilitation in the home environment has been discussed, but no work has addressed the practical problem of detecting basic body parts under different sensing conditions on a large scale. In this study, we evaluate the ability of the OpenPose pose estimation algorithm to perform keypoint detection of anatomical landmarks under different conditions. We infer the quality of detection based on the keypoint confidence values reported by the OpenPose. We used more than two thousand unique exercises for the evaluation. We focus on the influence of the camera view and the influence of the position of the trainees, which are essential in terms of the use for home exercise. Our results show that the position of the trainee has the greatest effect, in the following increasing order of suitability across all camera views: lying position, position on the knees, sitting position, and standing position. On the other hand, the effect of the camera view was only marginal, showing that the side view is having slightly worse results. The results might also indicate that the quality of detection of lower body joints is lower across all conditions than the quality of detection of upper body joints. In this practical overview, we present the possibilities and limitations of current camera-based systems in telerehabilitation.

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Telehealth Using PoseNet-Based System for In-Home Rehabilitation

Cited by 23 publications

References 29 publications

Empirical Mode Decomposition and Hilbert Spectrum for Abnormality Detection in Normal and Abnormal Walking Transitions

Empirical Mode Decomposition and Hilbert Spectrum for Abnormality Detection in Normal and Abnormal Walking Transitions

Development of Computer Vision-enabled Augmented Reality Games to Increase Motivation for Sports

Single Camera-Based Remote Physical Therapy: Verification on a Large Video Dataset

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