AI is at the heart of future medicine, from Diagnostic assistance, computer-assisted surgery, medical robots, predictive medicine, anticipation of an epidemic, patient triage, and development of new treatments. All these applies to Physical, Medical & Neurorehabilitation who faces challenges from various medical condition and diseases.
AI to better guide patients for neurorehabilitation
There is a huge potential for artificial intelligence (AI) and machine learning (ML) to revolutionize motor recovery in the field of rehabilitation medicine. They can assist in evaluating, diagnosing, and personalizing treatment plans for motor impairment patients. Wearable sensors, virtual and augmented reality, and robotic devices allow precise movement analysis and adaptive neurorehabilitation. AI-powered telerehabilitation makes remote monitoring and consultation possible. However, healthcare professionals must prioritize patient safety and interpret AI-generated insights. Further research is needed to determine their effectiveness in rehabilitation medicine.
Health monitoring:
Health monitoring is crucial in hospitals and rehabilitation centres. Challenges can affect the reliability and accuracy of health data. Human error, patient compliance concerns, time, money, technology, and environmental factors might cause these issues. In order to improve patient care, healthcare planners or providers must address these challenges.
There are systems generates real-time data that are stored in the cloud and are accessible to physical therapists and patients. Additionally, these system’s real-time dashboards provide a comprehensive analysis of the user’s gait and balance, enabling personalized training plans with tailored exercises and better rehabilitation outcomes.
Using non-invasive smart sensing technology, AI based rehab-solution enables healthcare facilities to monitor patients’ health and enhance their physical rehabilitation plans.
AI-based gait evaluation:
“Advanced movement analysis technologies have been developed to improve objectivity, accuracy, quantification, and sensitivity to disease-related changes of clinical assessments of gait and balance”
AI-based gait evaluation systems show a lot of potential for managing Parkinson’s disease and improving patient outcomes. These systems have the ability to change clinical decision-making and provide personalized therapies. However, further research is required to determine their effectiveness and refine their use.
AI can assist physical therapists in diagnosis, assessment, and treatment planning. It can also track patient data for predictive analytics, making physical therapy more accessible from home. Recent advances in AI technology have enhanced physical therapy.
Examples of AI application:
1. SWORD health:
This is an innovative system that empowers patients to receive physical rehabilitation from the comfort of their homes. By utilizing wireless motion trackers, a “digital therapist,” and patient data analytics, this system provides a comprehensive approach to rehabilitating patients. The result is a safe, effective, and convenient solution for patients who look for an alternative to traditional in-person therapy.
2. Digital Musculoskeletal Therapy:
Deep learning algorithms have the ability to analyze images and detect structural anomalies that are often undetectable to humans. This technology can be used by patients, practitioners, and providers to diagnose and treat musculoskeletal disorders effectively. Digital MSK has the potential to revolutionize the treatment of injuries or disorder related to muscles, nerves, tendons, joints, cartilage, and spinal discs. Once integrated into a cohesive platform, this technology can be used to great success.
3. Kemtai’s Motion Technology:
Kemtai’s Motion Intelligence Platform is an exercise tool ecosystem connect0ing users with personalized home fitness training. Using advanced computer vision and artificial intelligence, the platform provides real-time training feedback, making physiotherapy and fitness exercises safer and more effective. With Kemtai, users can access their training program on a browser or mobile application without needing expensive fitness equipment or accessories.
Concluding note:
Physiotherapy can be a difficult experience for both patients and physical therapists. The traditional approach involves subjective measurements and regular visits to the clinic, which makes it challenging to monitor progress. Patients may also face difficulty in reaching out to their physical therapists.
In contrast, AI-powered therapy allows patients to track their progress continuously and precisely. The therapist can analyze the patient’s progress through AI algorithms, allowing them to optimize treatment programs based on their needs. This means that they can efficiently work around any limitations or restrictions that may come up during their recovery, resulting in effective treatment and faster recovery.
To know more about AI applications for rehabilitation, connect with us (BNC) today, we can organize a demonstration.
Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5799707/
