Rule-Based Human Motion Tracking for Rehabilitation Exercises: Realtime Assessment, Feedback, and Guidance

Zhao, Wenbing; Reinthal, M. Ann; Espy, Deborah D.; Luo, Xiong

doi:10.1109/access.2017.2759801

Cited by 48 publications

(31 citation statements)

References 34 publications

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“…Thus, the technological implementation of an appropriate program of motor rehabilitation must involve an expert system that could substitute the therapist and provide the patient with feedback. Recent studies applied algorithms based on rules [17] or Dynamic Time Warping [18] for the recognition of therapeutic movements, and fuzzy logic [19] for the diagnosis of physical impairments. Nevertheless, the current systems are essentially able to discriminate between a correct and an incorrect gesture, but they do not give a targeted feedback on the type of error or they do not consider compensatory movements when an exercise is wrongly executed.…”

Section: Related Workmentioning

confidence: 99%

Implementation and Assessment of an Intelligent Motor Tele-Rehabilitation Platform

Rybarczyk

Pérez-Medina

Leconte³

et al. 2019

Electronics

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Over the past few years, software applications for medical assistance, including tele-rehabilitation, have known an increasing presence in the health arena. Despite the several therapeutic and economic advantages of this new paradigm, it is important to follow certain guidelines, in order to build a safe, useful, scalable, and ergonomic tool. This work proposes to address all these points, through the case study of a physical tele-rehabilitation platform for patients after hip replacement surgery. The scalability and versatility of the system is handled by the implementation of a modular architecture. The safeness and effectiveness of the tool is ensured by an artificial intelligence module that assesses the quality of the movements performed by the user. The usability of the application is evaluated by a cognitive walkthrough method. Results show that the system (i) is able to properly assess the correctness of the human’s motion through two possible methods (Dynamic Time Warping and Hidden Markov Model), and (ii) provides a good user experience. The discussion addresses (i) the advantages and disadvantages of the main approaches for a gesture recognition of therapeutic movements, and (ii) critical aspects to provide the patient with the best usability of a tele-rehabilitation platform.

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Section: Related Workmentioning

confidence: 99%

Implementation and Assessment of an Intelligent Motor Tele-Rehabilitation Platform

Rybarczyk

Pérez-Medina

Leconte³

et al. 2019

Electronics

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“…This makes installation, distribution, and multi-site use arduous. Some applications offer a convoluted strategy to define and update exercise parameters, such as configuration files defined in the eXtensible Markup Language (XML) or direct editing of the game development interface [38]. This approach does not allow exercise parameters such as the joints involved, direction of rotation, and number of repetitions to be updated easily.…”

Section: Related Work and Contributionsmentioning

confidence: 99%

ExerciseCheck

Pandit

Tran

et al. 2019

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

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ExerciseCheck is a scalable, accessible platform designed and developed for the remote monitoring and evaluation of physical therapy. Physical rehabilitation is an important aspect of a patient's recovery from injury and often requires the patient to perform a prescribed set of exercises over medium-to long-term periods. In the absence of a physical therapist, using a low-cost, non-intrusive solution can serve as a complement to in-clinic sessions and provide patients with valuable insights into their exercises. We present the design, implementation, and deployment of ExerciseCheck, a modular system that incorporates machine learning techniques with contemporary web technologies to enable a user-friendly experience for patients and physical therapists. Initially a proof-of-concept, the latest version of ExerciseCheck is now deployed as a hybrid desktop and web application at a Boston University rehabilitation clinic and has been employed by physical therapists in their sessions with individuals with Parkinson's disease. We provide insights into the usability requirements, architecture design, and implementation challenges of the development and deployment of a productionquality platform for remote physical therapy in a clinical setting. CCS CONCEPTS • Human-centered computing → Activity centered design; Interaction design process and methods; Human computer interaction (HCI); User centered design; • Hardware → Sensors and actuators;

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“…The rule-based approach is less computationally intensive and could capture precise information regarding the detected activity, such as the back-flexion angle. For PACTS, we choose to follow a rule-based approach that we developed previously [6,[10][11][12]. It fits better with the requirement for PACTS than a competing rule-based approach [13] because our rule-based framework could dynamically determine the starting and ending frame of an activity, and it can be integrated seamlessly with our alerting mechanism.…”

Section: Background and Related Workmentioning

confidence: 99%

“…The Activity Recognizer component in the KinectSever is used to recognize the registration gesture and to detect predefined activities, which are defined in the Configuration file encoded in the eXtensible Markup Language (XML). Both the gesture/activity description and the recognition engine follow the framework that we developed previously [10][11][12]. In this framework, an activity can be defined in terms of Joint Angle, Joint Distance, and Bone Orientation.…”

Section: Gesture Recognition and Activity Detectionmentioning

confidence: 99%

Design, Implementation, and Field Testing of a Privacy-Aware Compliance Tracking System for Bedside Care in Nursing Homes

Zhao

Reinthal

et al. 2017

ASI

Self Cite

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Lower back musculoskeletal disorders are pervasive in workplaces. In the United States alone, the total cost of such injuries exceed $100 billion a year. The lower-back injury rate in the healthcare sector is one of the highest among all industry sectors. A main risk factor for lower-back injuries is the use of improper body mechanics when doing lifting and pulling activities. In healthcare venues, nursing homes in particular, nursing assistants are on the front line to take care of patients. Even in places where ceiling-mounted lifting equipment is installed, they are still required to handle the patient for bedside care, such as sliding the sling underneath the patient, scooping up the patient, putting on compression socks, etc. To help nursing assistants get into the habit of using proper body mechanics, we designed and implemented a privacy-aware compliance tracking system (PACTS). PACTS can track a nursing assistant for possible violation of proper body mechanics while doing bedside care and provide realtime feedback via a smart wearable device such as a smart watch worn by the nursing assistant. The system was deployed in a local nursing home for an 80-day field study in six rooms with seven participating nursing assistants. The test exposed several issues with the original design of the system. The primary issue is how to balance the privacy requirement and the usability of the system. Overemphasizing the former would negatively impact the latter. This issue is partially resolved with a leasing mechanism where the system would automatically register a nursing assistant within the lease period once she or he has manually registered with the system.

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Rule-Based Human Motion Tracking for Rehabilitation Exercises: Realtime Assessment, Feedback, and Guidance

Cited by 48 publications

References 34 publications

Implementation and Assessment of an Intelligent Motor Tele-Rehabilitation Platform

Implementation and Assessment of an Intelligent Motor Tele-Rehabilitation Platform

ExerciseCheck

Design, Implementation, and Field Testing of a Privacy-Aware Compliance Tracking System for Bedside Care in Nursing Homes

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