A Serious Games Platform for Cognitive Rehabilitation with Preliminary Evaluation

A Multimodal Software Architecture for Serious Exergames and Its Use in Respiratory Rehabilitation

Serious Exergames (SEGs) have been little concerned with flexibility/equivalence, complementarity, and monitoring (functionalities of systems that deal with a wide variety of inputs). These functionalities are necessary for health SEGs due to the variety of treatments and measuring requirements. No known SEG architectures include these three functionalities altogether. In this paper, we present the 123-SGR software architecture for the creation of an SEG that is appropriate to the needs of professionals and patients in the area of rehabilitation. An existing SEG was adapted and therapy-related sensor devices (Pneumotachograph, Manovacuometer, Pressure Belt, and Oximeter) were built to help the patient interact with the SEG. The architecture allows the most varied input combinations, with and without fusion, and these combinations are possible for both conscious and unconscious signals. Health and Technology professionals have assessed the SEG and found that it had the functionalities of flexibility/equivalence, complementarity, and monitoring, and that these are really important and necessary functionalities. The 123-SGR architecture can be used as a blueprint for future SEG development.

Application of Serious Games in Health Care: Scoping Review and Bibliometric Analysis

Background

Serious games (SGs) as one kind of intervention that can improve the level of knowledge and change behavior to affect health outcomes has been increasingly applied in health care.

Objective

Analyze hotspots and trends of the application of SGs in health care and provide reference and direction for further research in the future.

Methods

The Web of Science (WoS) Core Collection database was used for extracting the literature on SGs in health care for the period from the database established to 11 October, 2021. Scoping review and bibliometric analysis were used to deeply analyze and visualize countries, categories of studies, annual study output, cited authors, cited journals, cited articles, and keywords of healthcare field.

Results

A total of 1,322 articles were retrieved, then every articles' title and abstract were read one by one, and 795 articles were included after screening with an exponential increase in publication volume. The United States of America made the greatest contribution to global publications regarding SGs in health care. From the total, 20.8% of articles fall under the category of health care sciences services. The target groups were mainly concentrated in children (18.0%), youth (13.8%), the elderly (10.9%), adolescents (9.1%), and adults (3.4%). Baranowski T (n = 103 citations) is the most influential author, followed by Kato PM (n = 73 citations) and Desmet A (n = 58 citations). The top three cited journals were "Plos One" (n = 268 citations), "Games for Health Journal" (n = 209 citations), and "Journal of Medical Internet Research" (n = 197 citations), and the top three cited articles were "A meta-analysis of serious digital games for healthy lifestyle promotion," "A Systematic Review of Serious Games in Training Health Care Professionals," and "Video game training enhances cognitive control in older adults." More and more studies focus on specific age groups, such as children, adolescents, and the elderly. The research hotspots and trends included "rehabilitation," "medical education," and "design."

Conclusions

The application of SGs in health care remains important areas for future research. "Rehabilitation," "medical education," and "design" reflected the latest research hotpots and future trends.

Adaptive Rehabilitation Bots in Serious Games

In recent years, we have witnessed a growing adoption of serious games in telerehabilitation by taking advantage of advanced multimedia technologies such as motion capture and virtual reality devices. Current serious game solutions for telerehabilitation suffer form lack of personalization and adaptiveness to patients' needs and performance. This paper introduces "RehaBot", a framework for adaptive generation of personalized serious games in the context of remote rehabilitation, using 3D motion tracking and virtual reality environments. A personalized and versatile gaming platform with embedded virtual assistants, called "Rehab bots", is created. Utilizing these rehab bots, all workout session scenes will include a guide with various sets of motions to direct patients towards performing the prescribed exercises correctly. Furthermore, the rehab bots employ a robust technique to adjust the workout difficulty level in real-time to match the patients' performance. This technique correlates and matches the patterns of the precalculated motions with patients' motions to produce a highly engaging gamified workout experience. Moreover, multimodal insights are passed to the users pointing out the joints that did not perform as anticipated along with suggestions to improve the current performance. A clinical study was conducted on patients dealing with chronic neck pain to prove the usability and effectiveness of our adjunctive online physiotherapy solution. Ten participants used the serious gaming platform, while four participants performed the traditional procedure with an active program for neck pain relief, for two weeks (10 min, 10 sessions/2 weeks). Feasibility and user experience measures were collected, and the results of experiments show that patients found our game-based adaptive solution engaging and effective, and most of them could achieve high accuracy in performing the personalized prescribed therapies.

Interaction Modalities Used on Serious Games for Upper Limb Rehabilitation: A Systematic Review

This systematic review aims to analyze the state-of-the-art regarding interaction modalities used on serious games for upper limb rehabilitation. A systematic search was performed in IEEE Xplore and Web of Science databases. PRISMA and QualSyst protocols were used to filter and assess the articles. Articles must meet the following inclusion criteria: they must be written in English; be at least four pages in length; use or develop serious games; focus on upper limb rehabilitation; and be published between 2007 and 2017. Of 121 articles initially retrieved, 33 articles met the inclusion criteria. Three interaction modalities were found: vision systems (42.4%), complementary vision systems (30.3%), and no-vision systems (27.2%). Vision systems and no-vision systems obtained a similar mean QualSyst (86%) followed by complementary vision systems (85.7%). Almost half of the studies used vision systems as the interaction modality (42.4%) and used the Kinect sensor to collect the body movements (48.48%). The shoulder was the most treated body part in the studies (19%). A key limitation of vision systems and complementary vision systems is that their device performances might be affected by lighting conditions. A main limitation of the no-vision systems is that the range-of-motion in angles of the body movement might not be measured accurately. Due to a limited number of studies, fruitful areas for further research could be the following: serious games focused on finger rehabilitation and trauma injuries, game difficulty adaptation based on user's muscle strength and posture, and multisensor data fusion on interaction modalities.

The SonicHand Protocol for Rehabilitation of Hand Motor Function: A Validation and Feasibility Study

Musical sonification therapy is a new technique that can reinforce conventional rehabilitation treatments by increasing therapy intensity and engagement through challenging and motivating exercises. The aim of this paper is to evaluate the feasibility and validity of the SonicHand protocol, a new training and assessment method for the rehabilitation of hand function. The study was conducted in 15 healthy individuals and 15 stroke patients. The feasibility of implementation of the training protocol was tested in stroke patients only, who practiced a series of exercises concurrently to music sequences produced by specific movements. The assessment protocol evaluated hand motor performance during pronation/supination, wrist horizontal flexion/extension, and hand grasp without sonification. From hand position data, 15 quantitative parameters were computed evaluating mean velocity, movement smoothness, and angular excursions of hand/fingers. We validated this assessment in terms of its ability to discriminate between patients and healthy subjects, test-retest reliability and concurrent validity with the upper limb section of the Fugl-Meyer scale (FM), the functional independence measure (FIM), and the Box and Block Test (BBT). All patients showed a good understanding of the assigned tasks and were able to correctly execute the proposed training protocol, confirming its feasibility. A moderate-to-excellent intraclass correlation coefficient was found in 8/15 computed parameters. The moderate-to-strong correlation was found between the measured parameters and the clinical scales. The SonicHand training protocol is feasible and the assessment protocol showed good to excellent between-group discrimination ability, reliability, and concurrent validity, thus enabling the implementation of new personalized and motivating training programs employing sonification for the rehabilitation of hand function.