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AI in rehab tech

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Dr Chen-onn Leong discusses the role of artificial intelligence (AI) and machine learning in the ongoing development of rehabilitation technology – could we be looking at a future without therapists? 

 

Healthcare is no exception to the new era of possibilities brought about by the convergence of artificial intelligence (AI) and machine learning (ML). 

These revolutionary technologies have shown great promise in the field of rehabilitation for helping people recover from illnesses, disabilities, and cognitive impairments. 

With AI and robotics making rapid advancements, a fascinating discussion over whether these technologies might eventually replace human therapists develops. 

In this in-depth article, prepared to help further advance the work of MotusAcademy and its collaborative network, we examine the varied applications of AI and ML in rehabilitation technologies and ponder the alluring idea of an age in which robots and AI take centre stage and perhaps even supplant therapists.

1) Unveiling the Power of AI and ML in Rehabilitation:

1.1 Innovating Rehabilitation Technologies and Assistive Devices:

AI and ML algorithms, at the forefront of technical advancements, are driving the creation of advanced rehabilitation and assistive technologies. These technologies enable an unmatched analysis of user movement data through the integration of sensors, actuators, and state-of-the-art AI algorithms, promoting improved control and natural interactions. Such development provides enhanced precision and accuracy of the system and improves the effectiveness of rehabilitation interventions, contributing to better patient outcomes [1].

1.2 Revolutionising Cognitive Rehabilitation:

AI and ML algorithms are driving the development of tailored programmes that target certain impairments, like memory loss, attention difficulties, and executive dysfunction. These adaptive algorithms enable customised training regimens and offer priceless feedback for maximising cognitive recuperation by dynamically adjusting the program’s difficulty level based on the user’s performance [2]. 

A recent study found that older persons with mild cognitive impairment who underwent memory training with the help of a humanoid social robot improved in therapeutic behaviour, and visual gazing, and had a decrease in depressive symptoms. Future instruments for cognitive training and help should employ physically embodied AI robots since they are practical and efficient [3].

1.3 Unlocking the Potential of Virtual Reality and Gamification

Rehabilitation programmes are now integrated with the immersive world of virtual reality (VR) and gamification techniques thanks to the power of AI and ML. These fascinating technologies provide patients with lifelike simulations that let them participate in daily activities in a virtual setting. As ML algorithms meticulously analyse performance data, they offer vital real-time biofeedback and make it possible to follow development and progress in great detail [4]. 

In addition to VR, augmented reality (AR) can also be used in rehabilitation thanks to AI and ML [5]. By superimposing computer-generated sensory data on the real environment, AR gives patients engaging, immersive experiences. AI systems examine patient responses and sensor data in real-time, enabling quick alterations in the AR environment to improve training and therapeutic results.

Figure 1: Immersive rehabilitation system incorporated with advanced rehabilitation robotics and digital assessment tools through the power of AI and ML

2) Unravelling the Advantages of AI and ML in Rehabilitation:

2.1. Unparalleled Individualised Care:

AI and ML algorithms can efficiently utilise the massive reservoirs of patient data, which includes medical records, imaging scans, and sensor data from multiple sources, to develop highly customised treatment regimens. These customised plans consider unique traits, preferences, and response patterns, adjusting the treatment strategy to meet the individual needs of each client [6]. The algorithms are excellent at identifying complex correlations and patterns that frequently escape human therapists, enabling interventions that are carefully catered to and extremely effective.

2.2. The Strength of Constant Monitoring and Feedback

Continuous monitoring and feedback are made possible by seamlessly integrating AI-enabled rehabilitation technology and wearables. Real-time tracking of patients’ progress enables therapists to remotely supervise and modify treatment regimens based on data. This paradigm change increases productivity by minimising the need for frequent in-person encounters and improving patient outcomes [7].

2.3. Data-driven Predictive Models and Analytics

Through real-time monitoring and patient extensive historical data, AI & ML algorithms can analyse and identify patterns and trends to build data-driven predictive algorithms that may allow therapists to have access to models that forecast a patient’s possible course of recovery [6]. 

These models may assist therapists in establishing reasonable objectives, selecting appropriate treatment modifications, and skillfully controlling patient expectations. Such a model can also be analytical and enable the detection of potential risks of specific conditions or forecast the possibility of complications. As a result, early intervention and proactive treatment planning are made possible, which helps people undergoing rehabilitation stop the progression of disability and improves their long-term prognosis [8].

2.4 Collaborative Rehabilitation Networks

The development of cooperative networks between therapists, researchers, and rehabilitation facilities is made possible by AI and ML technology [9]. These networks enable the exchange of information, best practices, and treatment guidelines, building a community of learners. Rehabilitation specialists can use AI capabilities to continuously raise the standard and efficacy of care provided to patients by combining their resources and knowledge.

2.5 Continuous Learning and Adaptation

The ability of AI and ML to continuously learn and adapt in response to new data is one of its main advantages [8]. This feature can be used by rehabilitation systems to continuously enhance their performance, fine-tune treatment strategies, and modify interventions in real time. AI systems gain expertise and personalization over time by learning from a wide range of patient scenarios, providing increasingly specialised and efficient rehabilitation solutions.

2.6 Promoting Affordability and Accessibility.

Robotics and AI in rehabilitation technology have the potential to completely change how accessible therapy services are. Through telerehabilitation platforms, physical boundaries are broken down and remote therapeutic sessions are made possible. Aside from that, AI-driven technology might offer less expensive alternatives to traditional therapy approaches, making rehabilitation more accessible and long-lasting [10].

3) Picturing the Future: AI and Robotics in Rehabilitation:

3.1 Augmenting therapist-AI-robot Cooperation

The future of rehabilitation is more likely to see human therapists’ jobs being enhanced and expanded through a symbiotic relationship with AI and robotics than being rendered obsolete. AI technologies can reduce the administrative responsibilities experienced by therapists, allowing them to devote more time to complex and individualised elements of patient care by automating repetitive procedures and delivering evidence-based insights. Combining the benefits of human expertise and AI capabilities, therapists and AI systems may make collaborative clinical decisions to build and optimise treatment regimens, as well as thereby improving the overall effectiveness of rehabilitation therapies [11].

Figure 2: The potential for Therapist-AI collaboration allows objective and consistent decision-making in planning and managing patients’ rehabilitation journey as well as providing better prediction accuracy and effective assessment for patients.

3.2 Ethical Considerations and Creating the Foundation for Responsible Implementation:

As we explore the integration of AI and robotics in rehabilitation, it is imperative to address several ethical issues. The need to protect patient privacy, guarantee data security, reduce algorithmic biases, and avoid dehumanisation of care cannot be overstated. The healthcare sector has a complex problem with data accessibility due to the confidentiality of patient records and the customary reluctance of healthcare providers to share personal data. 

To ensure the fair and moral application of these technologies in the field of rehabilitation, responsible legislation, policy and rules must be established at the international level. To safeguard patient confidentiality and uphold trust, strict data privacy policies, informed consent processes, and secure data storage technologies should be put in place. 

Additionally, efforts should be made to provide fair access to rehabilitation services across various populations and to reduce algorithmic biases. Since AI and ML need large datasets to continuously learn and correctly categorise or forecast a variety of tasks, such issues of data privacy and security may hinder the progress of such development [6].

3.3 Explainable AI

Machine learning algorithms’ output and outcomes can now be understood and trusted by human users thanks to a set of procedures and techniques known as explainable artificial intelligence (XAI) and it is currently incorporated in big tech firms’ systems such as Google or Microsoft. Understanding the choices that deep learning-based AI systems make is essential as these systems become more complicated. With the help of XAI approaches, therapists and patients will be able to understand the rationale behind the system’s recommendations and actions. AI in rehabilitation will potentially be kept accountable, dependable, and trustworthy thanks to XAI [6].

3.4 Integration with the Internet of Things (IoT) and Empowering Patient Engagement

The combination of AI and ML with IoT devices has enormous potential for rehabilitation. IoT sensors that are included in commonplace items like clothing, smart home gadgets, or home medical equipment can gather insightful information on patients’ movements, activities, and adherence to therapy. These data can be examined by AI algorithms, which can then prompt rapid interventions where necessary and real-time insights. 

Such integration, when combined with user-friendly interfaces, wearable tech, and mobile apps, has the potential to provide patients with more control over their recovery processes. Patients can actively take part in their care, keep track of their development, and get tailored feedback. Better adherence to therapy programmes, higher motivation levels, and enhanced general well-being are all influenced by this increased engagement and autonomy.

3.5 Overcoming Cultural and Language Barriers:

The creation of gamified systems that are accessible, inclusive in design and culturally appropriate to a particular region is still a challenge due to cultural and linguistic hurdles faced by rehabilitation technology manufacturers [12, 13]. 

AI-enabled tools for language translation and cultural adaptation can facilitate communication and understanding between therapists and patients from varied cultural backgrounds in the context of rehabilitation. By reducing language barriers, AI technology enables therapists to provide more thorough and culturally sensitive care, ensuring that rehabilitation programmes are effective for patients from all backgrounds. In addition, with the wide availability of AI translating tools in the market, interpreting and comprehending a publication’s essential concepts in the large number of non-English research publications covering rehabilitation, that is of high quality, is becoming less of a challenge [14].

3.6 The “Human Touch”

Beyond their technical proficiency, we have to embrace the fact that human therapists offer unique qualities of therapy that are irreplaceable. AI systems are unable to simply mimic the substantial effects of emotional support, empathy, and the therapeutic relationship developed between therapists and patients. The capability to replicate realistic human personality, demeanour and gestures in AI and robots similar to those in science fictional movies like “Star Wars” or “WALL-E” are still many light years away. In the rehabilitation process, the rapport and personal connection that a therapist builds with their patient are essential for promoting motivation, compliance, and general wellbeing.

3.7 Navigating Complexity and Adaptability:

Rehabilitation frequently requires complex relationships that call for instantaneous adaptability depending on subtle physical and emotional cues. Human therapists can notice subtle variations in their patients’ conditions, make quick adjustments, and react to unforeseen circumstances. Even though AI and robotics are excellent at data analysis and prediction, they might not be able to match the human intuition and agility needed in these dynamic rehabilitation environments [15].

Figure 3: Personal interaction between therapist and patient is an essential element in guiding and motivating patient in their recovery process. Human capability to adapt to any dynamic situation during rehabilitation also increases patient’s confidence in interacting safely with rehabilitation robotics.

Conclusion:

A new era of potential in rehabilitation technologies has arrived thanks to AI and ML. It is apparent that AI and robotics have the potential to improve personalised care, ongoing monitoring, and accessibility, but it is still unlikely that they will ever completely replace human therapists. A future when human therapists and AI systems work together and synergistically is more likely. It is difficult for AI systems to mimic the emotional support, flexibility, and complicated decision-making skills that human therapists bring to the table.

“Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last, unless we learn how to avoid the risks.” Stephen Hawkings.

Referring to the quote above by Stephen Hawkings, a future where human touch and expertise coexist peacefully with the power of technology will be shaped by the responsible integration of AI and robotics in rehabilitation. This will empower therapists, improve patient outcomes, and give them more control. 

Nonetheless, to discover new opportunities, it is crucial to conduct ongoing research and innovation in the fast-growing field of AI and ML in rehabilitation. To create an environment that supports experimentation, validation, and the creation of strong standards for the deployment of AI and robotics in rehabilitation, the collaboration between academic institutions, healthcare organisations, technology businesses, and regulatory agencies is essential.

Last but not least, we should not fear the advancement of AI or the possibility of it ever replacing humans in any field. Instead, let us embrace and keep up with this progress by learning and acquiring new skills that branch out from these advancements, making us irreplaceable.

References:

[1] de Freitas MP, Piai VA, Farias RH, Fernandes AM, de Moraes Rossetto AG, Leithardt VRQ. Artificial Intelligence of Things Applied to Assistive Technology: A Systematic Literature Review. Sensors. 2022;22(21):8531.

[2] Yuan F, Klavon E, Liu Z, Lopez RP, Zhao X. A systematic review of robotic rehabilitation for cognitive training. Frontiers in Robotics and AI. 2021;8:605715.

[3] Pino O, Palestra G, Trevino R, De Carolis B. The humanoid robot NAO as trainer in a memory program for elderly people with mild cognitive impairment. International Journal of Social Robotics. 2020;12:21-33.

[4] Kanade A, Sharma M, Manivannan M. Virtual Reality, Robotics, and Artificial Intelligence: Technological Interventions in Stroke Rehabilitation.  The Internet of Medical Things (IoMT) and Telemedicine Frameworks and Applications: IGI Global; 2023. p. 105-23.

[5] Korn O, Buchweitz L, Rees A, Bieber G, Werner C, Hauer K, editors. Using augmented reality and gamification to empower rehabilitation activities and elderly persons. a study applying design thinking. Advances in Artificial Intelligence, Software and Systems Engineering: Joint Proceedings of the AHFE 2018 International Conference on Human Factors in Artificial Intelligence and Social Computing, Software and Systems Engineering, The Human Side of Service Engineering and Human Factors in Energy, July 21–25, 2018, Loews Sapphire Falls Resort at Universal Studios, Orlando, Florida, USA 9; 2019: Springer.

[6] Al Kuwaiti A, Nazer K, Al-Reedy A, Al-Shehri S, Al-Muhanna A, Subbarayalu AV, et al. A Review of the Role of Artificial Intelligence in Healthcare. Journal of Personalized Medicine. 2023;13(6):951.

[7] Nascimento LMSd, Bonfati LV, Freitas MLB, Mendes Junior JJA, Siqueira HV, Stevan Jr SL. Sensors and systems for physical rehabilitation and health monitoring—A review. Sensors. 2020;20(15):4063.

[8] Myers TG, Ramkumar PN, Ricciardi BF, Urish KL, Kipper J, Ketonis C. Artificial intelligence and orthopaedics: an introduction for clinicians. The Journal of bone and joint surgery American volume. 2020;102(9):830.

[9] Secinaro S, Calandra D, Secinaro A, Muthurangu V, Biancone P. The role of artificial intelligence in healthcare: a structured literature review. BMC medical informatics and decision making. 2021;21:1-23.

[10] Pramuka M, Van Roosmalen L. Telerehabilitation technologies: Accessibility and usability. International journal of telerehabilitation. 2009;1(1):85.

[11] Lee MH, Siewiorek DP, Smailagic A, Bernardino A, Bermúdez i Badia S, editors. A human-ai collaborative approach for clinical decision making on rehabilitation assessment. Proceedings of the 2021 CHI conference on human factors in computing systems; 2021.

[12] Damaševičius R, Maskeliūnas R, Blažauskas T. Serious games and gamification in healthcare: a meta-review. Information. 2023;14(2):105.

[13] Nichol L, Pitt R, Wallace SJ, Rodriguez AD, Hill AJ. “There are endless areas that they can use it for”: speech-language pathologist perspectives of technology support for aphasia self-management. Disability and Rehabilitation: Assistive Technology. 2022:1-16.

[14] Meneghini R, Packer AL. Is there science beyond English? Initiatives to increase the quality and visibility of non‐English publications might help to break down language barriers in scientific communication. EMBO reports. 2007;8(2):112-6.

[15] Banks J. The human touch: practical and ethical implications of putting AI and robotics to work for patients. IEEE pulse. 2018;9(3):15-8.

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