Artificial Intelligence (AI) - Boon or Bane for Physiotherapy

One way to conceptualise Artificial Intelligence (AI) is as the ‘fourth industrial revolution’ and the next big thing in health care. AI is the ability of a computer to carry out useful work under the astute supervision of humans. Algorithms are used by AI to learn, think, and eventually support a variety of clinical procedures, including radiology and rehabilitation. AI is also utilised to locate all pertinent, up-to-date information from books, journals, and evidence-based practice, which supports clinical decision-making in the medical field. Additionally, AI technology helps to lower the number of medical errors in healthcare procedures.

The application of AI technologies in healthcare and rehabilitation is expanding quickly. In order to deliver optimal patient care, it is imperative that we, as healthcare practitioners, enhance our understanding of AI’s applications in rehabilitation.

Studies now underway on the use of AI in sports medicine and orthopaedic surgery indicate potential in assessing patient-reported outcomes, interpreting medical imaging, and forecasting the likelihood of athlete injuries. But like with anything new, this new technology will necessitate a basic understanding of the advantages, restrictions, and uses of AI-based technologies.

AI in rehabilitation can improve patient care by supporting physiotherapists in a number of ways, such as by conducting a comprehensive assessment, predicting patients’ performance, and making a diagnosis. AI can be used in problem-solving, x-ray diagnostics, and best-practice guidelines in medical and rehabilitative settings.

A wide range of clinical issues pertaining to the brain are being resolved with the aid of AI approaches. Our knowledge of complex brain mechanisms is being aided by the development of an increasing number of efficient algorithms through recent research and the accumulation of pertinent data. AI has a lot of promise for neurologic physical therapy. AI is being developed for applications such as robotic-assisted therapy, motor function and gait assessment, client level of function assessment, upper extremity rehabilitation, and movement assessment. As an illustration, consider the use of wearable sensor data to identify aberrant or asymmetrical walking patterns. AI sensors can identify aberrant movement patterns during functional movements and are a valuable tool for functional task analysis and the creation of individualised therapy programmes. This might be a great approach to keep an eye on the kind and quantity of workouts done at home in the future when combined with telerehabilitation, virtual reality, and body-worn sensors. For example, a remote therapist may receive notifications when a patient is not doing exercises correctly or when there are safety issues.

As professionals, we will need to adapt to these developments and understand how to make the most of AI. We may discover that, in order to succeed in our line of work, we must be able to analyse and interpret AI-generated algorithms, apply judgement to them, and integrate this AI into our practice in ethical, professional, and social contexts rather than acquiring more sophisticated manual therapy techniques or honing our diagnostic abilities. We face the possibility that machine intelligence will make decisions for us rather than just informing them if we don’t participate in the AI discourse and put it into reality. To improve our results, we need to collaborate with AI and humans.

For students and rehabilitation professionals to properly comprehend and utilise AI technology, they must possess AI literacy. The growing need for rehabilitation services across the globe has led to a constant evolution in the field of rehabilitation. Rehabilitation professionals are filling in the gaps in the field where AI is used globally to help with evaluation, personalised feedback for rehabilitation exercises, increased accessibility through virtual reality and telerehabilitation, and improved diagnosis and treatment efficiency for physicians and therapists. Rehabilitation professionals that possess AI literacy will be better equipped to assess online health information critically and counteract the infodemic of rehabilitation-related issues.

Regarding the application of AI in rehabilitation treatment, there are certain misconceptions. There are many who think AI will eventually take the position of licenced therapists, which could negatively impact patient treatment. This is untrue, though. AI is a technology that aids therapists in monitoring patient development, giving tailored feedback, and improving the efficacy of interventions. Furthermore, some believe that integrating AI into rehabilitative settings would be too costly and complex. But as technology develops, AI is becoming more widely available, more reasonably priced, and simpler to incorporate into current systems.

The argument that AI is not reliable is untrue because AI systems are developed and assessed according to strict guidelines, incorporating input from a variety of stakeholders and taking ethics into account. However, it is also critical to remember that, in order to guarantee appropriate AI integration, more stringent review procedures, ethical concerns, ongoing research and development, and stakeholder involvement are all necessary.

In the healthcare sector, AI is quickly becoming a game-changing technology globally. AI has the ability to address the ongoing issues of insufficient human resources, restricted access to high-quality healthcare systems, and communicable illnesses. It is anticipated that the use of AI in low resource or remote areas will significantly affect healthcare delivery and health outcomes, furthering the global goal of attaining universal health coverage.

AI-driven rehabilitation technologies are being created to aid with patients’ recovery from diseases, injuries, and impairments. These resources are particularly useful in places where access to rehabilitation facilities is restricted and there is a scarcity of rehabilitation professionals. Wearable technology, smartphone apps, and virtual reality systems are examples of AI-powered rehabilitation technologies that assist patients in tracking their progress and performing exercises. This can enhance patient outcomes, lower medical expenses, and expand access to high-quality rehabilitation programmes.

Physiotherapy, whether for sports injuries, chronic ailments, or other concerns, is a crucial component of patient care and rehabilitation from musculoskeletal (MSK) disorders. The ability to monitor a patient’s posture and movement patterns can help guide and correct them during prescribed exercises, assess the effectiveness of a treatment plan, and provide valuable information for future interventions. Traditionally, this has been accomplished in-person or through passive assistance with regular videos on computers, smartphones, or tablets, or with paper instructions. However, new technology driven by AI is altering that. Although AI in MSK and physiotherapy is still a relatively new idea, it has the potential to completely change the way we treat medical conditions. With real-time feedback and remedial instructions on patient movement, the technology can assist physicians optimise treatment regimens based on patient data and enhance patient outcomes.

AI-enabled physiotherapy uses computer vision for human motion analysis, pushing the boundaries of motion tracking technologies. During musculoskeletal physiotherapy exercises, this technology can precisely record movement patterns in real-time without requiring physical contact with the patient. This technology not only improves clinic efficiency globally but also provides insights that may lead to more effective treatments.

The inability of traditional human-interaction based physiotherapists to regularly supervise their patients and make sure they are performing their at-home exercise regimen appropriately is a major drawback. Because of this, many patients with musculoskeletal injuries find that traditional physiotherapy is an ineffective treatment. This is where AI in physiotherapy might help. Technologies like Kemtai motion-tracking, which use regular webcams on computers, phones, or tablets, may record every move patients make while exercising at home, converting any gadget with a camera into a virtual therapist.

New digital motion-capture systems have surfaced in recent years; these systems track a user’s movements and can score or fix them using sensors. Although sensor-based motion tracking for MSK and physiotherapy is a major advancement, these systems have a number of disadvantages. Low adherence rates are caused by a number of factors, including the cost of the device, low precision from the few sensors, and the difficulty patients have placing the sensors manually.

Other systems track movement using optical motion capture technology, which is based on light or reflection-based markers that are affixed to the subject’s body. These systems are difficult to place markers in and are prone to tracking mistakes due to occlusion, which is a barrier in the line of sight, and ghosting, caused by reflections. Many people view motion capture as an expensive procedure due to the technological and logistical difficulty required with sensor or marker-based motion capture, but with the correct tools and technology, it might be considerably more accessible. AI motion tracking enables motion capture without the need for physical markers or extra equipment by combining computer vision and machine learning.

Compared to the conventional physiotherapy we are accustomed to, AI physiotherapy offers numerous advantages. This is particularly true for individuals with long-term pain or injuries that necessitate regular home exercise following a recommended home exercise regimen in addition to frequent medical interventions. In these situations, AI physical therapy can assist shorten treatment durations, improve the precision and coherence of treatment regimens, and ensure that human error never occur again.

AI-guided at-home workouts can offer therapy that is comparable to, or superior to, having a physical therapist come to your house and demonstrate the proper movements. Exercises from musculoskeletal physical therapy are essential for MSK healing and rehabilitation. As a result, real-time feedback and remedial coaching improves the patient’s and therapist’s adherence to online physiotherapy exercises and significantly boosts the effectiveness of remote physical treatment.

AI physiotherapy can be utilised as a preventative measure for injuries or as a support during recovery because it is available around-the clock. Patients find it easier to maintain their workout regimen whenever they have time because it is essentially a 24/7 on-demand service. Appointments can be arranged flexibly since therapy is modified in response to patient progress, which is tracked via remote technology. Patients who struggle to make appointments won’t ever feel as though they are skipping out on treatment.

AI-based remote physical therapy not only tracks progress and offers real-time corrective feedback, but also makes it easy for patients to communicate with their therapist whenever it is convenient for them. Additionally, it offers quantitative measurement of their real progress and a consistent, dependable interface when the therapist is not physically there. This indicates that the patient has a sense of complete inclusion in their healing process and is able to readily communicate pertinent information to their physicians, family, and other healthcare providers as needed.

With digital MSK, a human therapist doesn’t need to perform any manual labour in order to treat a large number of patients quickly. It can be applied to improve the effectiveness and efficiency of a patient’s recuperation process and, in many situations, do away with the necessity for human intervention.

Machine learning and computer vision have great promise for revolutionising the treatment of MSK disorders. An excellent illustration is the ability of deep learning algorithms to identify structural abnormalities in photos that are imperceptible to humans and suggest remedial measures. When combined into a single, user-friendly platform, the technology can be effectively utilised by practitioners, patients, and providers. The way that musculoskeletal conditions like arthritis are treated may change as a result of digital MSK.

The field of remote physical treatment is expanding. It is one of the most exciting uses of AI in medicine that exists now. Research has demonstrated that distance therapy has numerous advantages over conventional types of treatment and can be just as effective or perhaps more so than in-person therapy. In addition to providing patients who live far from their physical therapists or do not have insurance that covers frequent trips to a clinic or hospital with easier access to care, it also allows the best possible course of rehabilitation through adaptive guidance and feedback backed by AI.

AI is transforming physical therapy, and this is for the better. Physiotherapists will employ intelligent assistants more frequently as the field grows more tech-savvy in order to improve the efficiency and accessibility of their work. AI has shown great promise in a variety of applications. It can be utilised for remote therapy via digital MSK or for autonomous rehabilitation programmes that track patients during their recuperation.