Background: Robot-assisted therapy has become a promising technology in the field of rehabilitation for poststroke patients with motor disorders. Motivation during the rehabilitation process is a top priority for most stroke survivors. With current advancements in technology there has been the introduction of virtual reality (VR), augmented reality (AR), customizable games, or a combination thereof, that aid robotic therapy in retaining, or increasing the interests of, patients so they keep performing their exercises. However, there are gaps in the evidence regarding the transition from clinical rehabilitation to home-based therapy which calls for an updated synthesis of the literature that showcases this trend. The present review proposes a categorization of these studies according to technologies used, and details research in both upper limb and lower limb applications. Objective: The goal of this work was to review the practices and technologies implemented in the rehabilitation of poststroke patients. It aims to assess the effectiveness of exoskeleton robotics in conjunction with any of the three technologies (VR, AR, or gamification) in improving activity and participation in poststroke survivors. Methods: A systematic search of the literature on exoskeleton robotics applied with any of the three technologies of interest (VR, AR, or gamification) was performed in the following databases: MEDLINE, EMBASE, Science Direct & The Cochrane Library. Exoskeleton-based studies that did not include any VR, AR or gamification elements were excluded, but publications from the years 2010 to 2017 were included. Results in the form of improvements in the patients’ condition were also recorded and taken into consideration in determining the effectiveness of any of the therapies on the patients. Results: Thirty studies were identified based on the inclusion criteria, and this included randomized controlled trials as well as exploratory research pieces. There were a total of about 385 participants across the various studies. The use of technologies such as VR-, AR-, or gamification-based exoskeletons could fill the transition from the clinic to a home-based setting. Our analysis showed that there were general improvements in the motor function of patients using the novel interfacing techniques with exoskeletons. This categorization of studies helps with understanding the scope of rehabilitation therapies that can be successfully arranged for home-based rehabilitation. Conclusions: Future studies are necessary to explore various types of customizable games required to retain or increase the motivation of patients going through the individual therapies.

Additive manufacturing (AM), an enabler of Industry 4.0, recently opened limitless possibilities in various sectors covering personal, industrial, medical, aviation and even extra-terrestrial applications. Although significant research thrust is prevalent on this topic, a detailed review covering the impact, status, and prospects of artificial intelligence (AI) in the manufacturing sector has been ignored in the literature. Therefore, this review provides comprehensive information on smart mechanisms and systems emphasizing additive, subtractive and/or hybrid manufacturing processes in a collaborative, predictive, decisive, and intelligent environment. Relevant electronic databases were searched, and 248 articles were selected for qualitative synthesis. Our review suggests that significant improvements are required in connectivity, data sensing, and collection to enhance both subtractive and additive technologies, though the pervasive use of AI by machines and software helps to automate processes. An intelligent system is highly recommended in both conventional and non-conventional subtractive manufacturing (SM) methods to monitor and inspect the workpiece conditions for defect detection and to control the machining strategies in response to instantaneous output. Similarly, AM product quality can be improved through the online monitoring of melt pool and defect formation using suitable sensing devices followed by process control using machine learning (ML) algorithms. Challenges in implementing intelligent additive and subtractive manufacturing systems are also discussed in the article. The challenges comprise difficulty in self-optimizing CNC systems considering real-time material property and tool condition, defect detections by in-situ AM process monitoring, issues of overfitting and underfitting data in ML models and expensive and complicated set-ups in hybrid manufacturing processes.

Aims and Objectives: Stroke is the main cause of long-term disability and happens mostly in the older population. Stroke affected patients experience either of the cognitive, visual or motor losses and recovery requires time and patience as they have to do physical exercises every day and at times repetitively. There are various types of stroke rehabilitation exercises focussing on technological solutions that include therapies performed using games. Motion-based games are popular in encouraging participants to perform repetitive tasks without being getting bored. Therefore, in this study, we have explored studies that included the use of games for stroke rehabilitation to understand the design principles and characteristics of the games used for these purposes. Method: A number of medical respositories were searched for relevant articles in a window of 2008-2018. 18 studies were chosen for the scoping review depending on the inclusion criteria, and design principles used in these studies are analysed and evaluated. Results and Conclusion: We present main findings from our review concerning the attributes of existing games for stroke rehabilitation such as meaningful play, handling of failures, emphasising challenge, and the value of feedback. We conclude with a list of design recommendations that future serious game developers can consider while designing interfaces for stroke patients.

The emergence of ChatGPT in higher education has raised immense discussion due to its versatility in performing tasks, including coding, personalized learning, human-like conversations, and information retrieval. Despite the rapidly growing use of ChatGPT, a dire need still exists for an overarching view regarding its role and implications in educational settings. Following the PRISMA guidelines, this study represents a systematic review of 26 articles exploring the use of ChatGPT in academic writing, personalized learning, and code generation. The relevant literature was identified through electronic databases, including Scopus, ACM Digital Library, Education Research Complete, Computers & Applied Sciences, Web of Science, and IEEE Xplore. Key details from each article were extracted and synthesized narratively to provide insights into ChatGPT’s efficacy in academic writing, personalized learning, and coding. The findings indicate that ChatGPT enhances tailored learning by adapting delivery methods to individual needs, supports academic writing through error detection and content refinement, and assists in coding by offering clarifications and reusable code snippets. However, there are concerns over its ethical implications, including the impact on academic integrity, overreliance by students on AI, and privacy concerns about data use. Based on these insights, this study proposes recommendations for the ethical and responsible integration of ChatGPT into higher education, ensuring its utility while maintaining academic integrity. In addition, the results are discussed based on the relevant learning theories to understand how students engage with, learn through, and adapt to AI technologies such as ChatGPT in educational contexts.

Background: Older adults face a unique set of challenges and may experience a range of psychological comorbidities. Digital storytelling is an emerging tool for sharing and recording lived experiences and may have the potential to support well-being but is yet to be systematically reviewed for use among older adults. Objective: The aim of this review is to examine the methods for creating digital stories, the health-related outcomes associated with creating digital stories, and the potential for implementing digital storytelling with older adults. Methods: We systematically searched electronic databases to identify articles published in English that reported on at least one health-related outcome of digital storytelling for participants aged ≥60 years. Data were extracted and synthesized using qualitative content analysis and summarized in tables. The methodological quality of the studies was assessed using the Mixed Methods Appraisal Tool. Results: A total of 8 studies were included in the review. Participants were primarily community-dwelling older adults living with dementia, involving family caregivers and professional care staff. Studies have taken various approaches to digital storytelling and reported diverse benefits associated with digital storytelling, including improvements in mood, memory, social engagement, and quality of relationships. Although the potential for implementation was not widely examined, some studies have presented evidence for acceptability and feasibility. Generally, studies were of high quality, despite the absence of comparator groups and confounder analyses. Conclusions: The evidence reviewed suggests that despite the various approaches taken, digital storytelling shows promise as an effective approach for supporting well-being in older adults. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42019145922; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019145922 International Registered Report Identifier (IRRID): RR2-10.2196/15512