Supporting therapists in motion-based gaming for brain injury rehabilitation

Putnam, Cynthia; Cheng, Jinghui; Rusch, Doris C.; Berthiaume, André; Burke, Robin

doi:10.1145/2468356.2468426

Cited by 5 publications

(5 citation statements)

References 4 publications

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“…Some studies incorporated perceptions of both patients and doctors [ 62 , 73 ] in developing their AI systems. Another study interviewed providers (therapists) about their experiences, opinions, expectations, and perceptions of a motion-based game for brain injury rehabilitation to guide the design of the proposed AI-based recommender system, which was a case-based reasoning (CBR) system [ 55 ]. The AI system ASSESS MS was also developed and evaluated based on users’ perceptions [ 48 ].…”

Section: Resultsmentioning

confidence: 99%

“…Some studies in our review performed usability testing of AI systems. For example, one study used AI to develop an adaptable CBR to help therapists ensure proper usability and functioning of CBR [ 55 ]. Guided by users’ needs, one study [ 27 ] developed an AI application (SMILY) to ensure good usability.…”

Section: Resultsmentioning

confidence: 99%

“…In this review, we identified studies that performed experiments involving clinicians and patients, and consecutively evaluated their AI system’s (eg, app, wearable device) interface [ 27 ], applicability [ 27 , 29 ], and appearance (anthropomorphism) [ 30 ] to ensure user-centeredness. Other studies [ 43 , 45 , 48 , 49 , 55 , 62 ] also addressed user requirements such as wearability and privacy concerns. A recent study further acknowledged the importance of a user-centered clinical field study, and identified external factors such as low lighting, expensive image annotation, and internet speed that can deter the effectiveness of AI systems for diagnosing diabetic retinopathy [ 75 ].…”

Section: Resultsmentioning

confidence: 99%

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Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review

Asan¹,

Choudhury²

2021

JMIR Hum Factors

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Background Despite advancements in artificial intelligence (AI) to develop prediction and classification models, little research has been devoted to real-world translations with a user-centered design approach. AI development studies in the health care context have often ignored two critical factors of ecological validity and human cognition, creating challenges at the interface with clinicians and the clinical environment. Objective The aim of this literature review was to investigate the contributions made by major human factors communities in health care AI applications. This review also discusses emerging research gaps, and provides future research directions to facilitate a safer and user-centered integration of AI into the clinical workflow. Methods We performed an extensive mapping review to capture all relevant articles published within the last 10 years in the major human factors journals and conference proceedings listed in the “Human Factors and Ergonomics” category of the Scopus Master List. In each published volume, we searched for studies reporting qualitative or quantitative findings in the context of AI in health care. Studies are discussed based on the key principles such as evaluating workload, usability, trust in technology, perception, and user-centered design. Results Forty-eight articles were included in the final review. Most of the studies emphasized user perception, the usability of AI-based devices or technologies, cognitive workload, and user’s trust in AI. The review revealed a nascent but growing body of literature focusing on augmenting health care AI; however, little effort has been made to ensure ecological validity with user-centered design approaches. Moreover, few studies (n=5 against clinical/baseline standards, n=5 against clinicians) compared their AI models against a standard measure. Conclusions Human factors researchers should actively be part of efforts in AI design and implementation, as well as dynamic assessments of AI systems’ effects on interaction, workflow, and patient outcomes. An AI system is part of a greater sociotechnical system. Investigators with human factors and ergonomics expertise are essential when defining the dynamic interaction of AI within each element, process, and result of the work system.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review

Asan¹,

Choudhury²

2021

JMIR Hum Factors

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“…Many contributions have consisted in a specialist choosing specific games for a given rehabilitation process [8] [16] [18]. The main limitation is that the customization of exercises is not considered [20], which represents a problem for specific patients. A solution appeared after the development of systems that offered specific exercises for specific lesions [10] [14].…”

Section: Related Workmentioning

confidence: 99%

Designing postures for rehabilitation therapies in a multimodal system based on a 3D virtual environment and movement-based interaction

Penichet

Lozano

Garrido

et al. 2022

Multimed Tools Appl

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Technological advances have facilitated new approaches to support different needs in healthcare environments. In particular, in the field of rehabilitation therapies, we can find software applications that have been developed to support the performance of specific exercises, often with different customization options. However, there are still many gaps that need to be addressed to provide more and better global solutions. In this article, we present a novel system aimed at physiotherapists, which allows them to create new rehabilitation exercises designed to meet the specific needs of their patients. This implies the creation of individualized therapies that contribute to a better and faster recovery of patients. The system consists of a virtual 3D environment with a 3D skeleton representing the patient. The physiotherapist can interact with the skeleton to design the desired postures that the patient should practice according to their personal limitations. The system allows physiotherapists to compose a complete and personalized set of exercises. Alternatively, the physiotherapist may also create the postures by means of a motion sensing device using motion- and voice-based interaction. Both options pose research challenges that the authors have addressed to provide the solution presented in this paper.

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“…There exist some systems which involve specialists in the development process of rehabilitation exercises [7]. If they need a specific exercise, they can request its development, but they are not able to design it themselves.…”

Section: Related Workmentioning

confidence: 99%

Virtual 3D Web Environment for Posture Design in Rehabilitation Using Kinect

Valls

Penichet

Lozano

2014

Proceedings of the 8th International Conference on Pervasive Computing Technologies for Healthcare

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Healthcare environments are considered an important scenario where new technologies play an important role in improving the rehabilitation process. Many software applications provide a way to rehabilitate patients and some of them also provide a degree of customization. Nevertheless, the physiotherapist is not always able to create new exercises and adapt them to the needs of a wide range of different patients. In this paper, we present an advanced proposal which primarily aims to provide the therapist with a tool for intuitive and easy design of specific rehabilitation postures for specific patients. The system consists of a skeleton in a virtual 3D environment which is composed of different joints with which the physiotherapist can interact in order to achieve the desired posture. It is also possible to design postures using Microsoft Kinect device thanks to its motion and voice interaction. Using 3D and Kinect device presents a number of development challenges that the authors have had to resolve, including movement of joints in the 3D space, the correlated movement of the different joints and matching within Kinect. Due to its development within a Web environment, these, and other features, make the system a powerful and place-independent tool.

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Supporting therapists in motion-based gaming for brain injury rehabilitation

Cited by 5 publications

References 4 publications

Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review

Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review

Designing postures for rehabilitation therapies in a multimodal system based on a 3D virtual environment and movement-based interaction

Virtual 3D Web Environment for Posture Design in Rehabilitation Using Kinect

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