Artificial Intelligence (AI) seems to be intertwined with everything we do these days. This is certainly true for healthcare. The potential benefits, such as cost savings, for instance, may cut healthcare costs in the US by about $150 billion in 2026. AI has also been incorporated into specific healthcare specialties such as physical therapy.
Physical therapy is integral to our healthcare system as it provides adjunctive care for musculoskeletal conditions and rehabilitation. Physical therapy can help increase your range of motion, decrease pain, enhance your flexibility, or improve overall musculoskeletal health. AI has expanded its role in physical therapy, intending to provide better and more efficient care.
However, some challenges may arise with this new technology, which deserves further exploration. Whether we are ready or not, AI is already a part of our lives. This article will discuss its implications in physical therapy and its impact on our musculoskeletal health.
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Understanding AI in Physical Therapy
AI is like giving machines the ability to think and learn, a bit like how humans do. But instead of brains, they use algorithms and data. The key components that allow AI to think and learn include machine learning, data analysis, and neural networks. Think of Machine Learning (ML) as the engine of AI. It’s a subset of AI that uses data to analyze and make predictions in healthcare. It helps to make decisions based on the patient’s own data and can provide immediate care solutions. Neural networks are like the brains of AI systems. They consist of layers of interconnected nodes to help AI make sense of complex data.
AI technologies have been integrated into physical therapy to help with the automation of clinical tasks. It uses technologies such as motion analysis, wearable devices, and virtual therapists to assist the physical therapy practice in patient care. AI can analyze how patients move and pinpoint problems in their movements through motion analysis. This technology has been developed recently with radar sensing systems, infrared, pressure sensors, and sound recognition and put into wearable devices.
Another AI-powered technology that physical therapists can utilize is virtual therapy (sometimes called tele-rehabilitation). Virtual therapists can help with triage and help answer basic questions that don’t warrant an actual visit while also providing assistance during out-of-office hours to provide guidance and support. All of these technologies make physical therapy more accessible to patients.
Transforming Rehabilitation with AI
AI is transforming rehabilitation with personalized treatment plans, virtual/augmented reality, and tele-rehabilitation. AI will use patient data to tailor rehabilitation regimens and continuously adapt therapies based on real-time progress monitoring. It will analyze a patient’s medical history, physical condition, and progress information to create personalized rehabilitation plans customized to their unique needs and abilities.
New immersive AI technologies like virtual reality (VR) and augmented reality (AR) are used to create engaging and interactive rehabilitation environments. With this technology, patients can manipulate the three-dimensional sensory environments in real time to help with their rehabilitation. It has been shown to help stroke survivors improve limb function and recover faster by simulating scenarios for cognitive and physical exercises.
Another exciting aspect of AI is that it enables remote rehabilitation through telemedicine. Patients can receive therapy sessions and guidance from video calls and AI-powered exercises from the comfort of their homes while allowing for practitioner monitoring remotely. Tele-rehabilitation through AI can help increase access to patients for long-term rehabilitative care. Evidence suggests that these VR-based interventions can provide more compliance and keep patients engaged longer, improving their health outcomes.
Enhancing Injury Prevention Through AI
Machine Learning and analytics have made it so that AI can enhance injury prevention. With ML, there are algorithms that use predictive analytics of the biomechanical data of patients to identify vulnerabilities. An example of this analysis is an ML-based fall risk tool assessment that produced early warning signs to help older adults prevent falls. These tools can use risk prediction as an early intervention strategy and help PTs create and monitor rehabilitation for their patients.
Preventing injuries has been made more efficient by combining wearable devices with AI-powered monitoring. These devices integrate sensors to track movement, posture, and muscle activity. The real-time feedback from the monitoring devices helps prevent overexertion and ensures that people are using the correct form. With this new technology, therapists can monitor their patient’s recovery process and compliance through direct visual and audio feedback of the assigned exercises.
Additionally, AI will compute the data to provide insights on optimizing training plans. It can keep a close eye on training loads and performance metrics to craft customized plans that minimize the risk of injuries. The use of AI in healthcare allows for a personalized approach to treatment that’s based on long-term monitoring through a data-driven manner to help with risk prevention, predictions, and interventions.
Challenges and Considerations of Using AI
Although the use of AI in healthcare comes with many benefits, there are still some challenges and considerations that need to be explored and addressed. AI is still an emerging resource that also comes with some potential implications that may need further mitigation. There are ethical concerns with AI-assisted healthcare in patient data privacy and security. There are also considerations for overall patient care with the need for human interaction for health.
Currently, a primary concern is that the laws don’t go far enough to protect patient privacy, as they can be hacked and used for malicious purposes. Another concern is that the human touch and understanding of human complexity can be lost with the use of AI, which can negatively impact health improvement. There is still uncertainty about the capability of AI’s applications in unpredictable scenarios that may arise and may need the understanding and experience of a human practitioner.
Other considerations of integrating AI into existing healthcare systems include training healthcare professionals to work with AI tools, addressing resistance to change, and other adoption barriers. According to a survey conducted on PTs, their knowledge of AI applications in rehabilitation was lower than their knowledge of AI in general. That study also revealed that PTs working in the nonacademic sector with less than ten years of experience had positive attitudes toward AI. This survey shows that some practitioners accept integrating AI into their practice. However, there’s still a need for additional training to enhance the knowledge of these healthcare professionals in AI applications.
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Summary
Whether you’re ready or not, AI technologies are already integrated into our healthcare systems and will continue to expand in this field. Within physical therapy, AI is used for the automation of clinical tasks, patient monitoring, remote rehabilitation, injury prevention, personalized treatment regimens, and many other clinical applications. These tools provide efficiency for practitioners, improve patient treatment compliance, and expand care access. However, concerns with legal implications such as privacy and protection, along with the potential negative impact of decreased human interaction with the integration of AI, still need to be addressed. These implications indicate the need for continued research, more education, and additional legal considerations to adequately incorporate AI use so that patients and practitioners reap the benefits while reducing the negative unintended consequences.
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