Gait rehabilitation is a critical therapeutic intervention aimed at improving or restoring walking ability in individuals affected by various impairments such as injuries, surgeries, neurological disorders, and chronic ailments. These conditions often lead to muscle weakness, spasticity, coordination loss, joint pain, and other challenges that hinder independent mobility and daily activities. Effective gait therapy not only restores normal walking patterns but also enhances balance, prevents falls, and improves overall functional capacity, thereby significantly enhancing patients' quality of life. In recent years, the integration of artificial intelligence (AI) has revolutionized gait rehabilitation by introducing advanced algorithms and technologies that personalize and optimize therapeutic interventions. AI techniques enable the analysis of complex gait patterns with precision and offer real-time feedback to both patients and therapists. By leveraging machine learning, AI systems can dynamically adapt rehabilitation protocols based on individual patient data collected from wearable sensors and other monitoring devices.
The goal of this special issue is to investigate the transformational influence of artificial intelligence (AI) on gait rehabilitation in order to improve therapeutic results for people who have mobility limitations due to accidents, surgeries, neurological diseases, or chronic illnesses. AI approaches enable exact analysis of complicated gait patterns and give real-time feedback to both patients and therapists, hence increasing the effectiveness of therapies. Using machine learning, AI systems may dynamically change rehabilitation regimens based on specific patient data from wearable sensors and other monitoring equipment. Finally, this special issue seeks to restore normal walking patterns, improve balance, avoid falls, and increase total functional ability, therefore greatly enhancing patients' quality of life.
This special issue, titled "Advancements in AI-Enhanced Gait Rehabilitation Techniques," aims to explore and highlight the latest developments, challenges, and future directions in the field of AI-driven gait rehabilitation. We invite researchers, clinicians, engineers, and industry professionals to contribute original research articles, review papers, case studies, and systematic reviews that advance our understanding and application of AI in enhancing gait rehabilitation.
Submissions may include, but are not limited to, the following topics:
1. Development and application of wearable sensors for real-time gait monitoring.
2. Predictive modelling for rehabilitation outcomes and patient progress.
3. AI-driven customization of rehabilitation protocols based on individual patient data.
4. AI-powered robotic exoskeletons and prosthetics that assist in gait training and rehabilitation.
5. Adaptive control systems in assistive devices for personalized support.
6. Utilization of VR and AR environments for immersive gait training experiences.
7. Development of AI-based tele-rehabilitation platforms for remote patient monitoring and intervention.
8. Real-world applications of AI-based gait rehabilitation techniques in various clinical settings.
9. Ethical issues surrounding the use of AI in gait rehabilitation, including patient privacy and data security.
Keywords:
Gait Analysis, Machine Learning, Biomechanics, Robotic Therapy, Rehabilitation Robotics
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
Gait rehabilitation is a critical therapeutic intervention aimed at improving or restoring walking ability in individuals affected by various impairments such as injuries, surgeries, neurological disorders, and chronic ailments. These conditions often lead to muscle weakness, spasticity, coordination loss, joint pain, and other challenges that hinder independent mobility and daily activities. Effective gait therapy not only restores normal walking patterns but also enhances balance, prevents falls, and improves overall functional capacity, thereby significantly enhancing patients' quality of life. In recent years, the integration of artificial intelligence (AI) has revolutionized gait rehabilitation by introducing advanced algorithms and technologies that personalize and optimize therapeutic interventions. AI techniques enable the analysis of complex gait patterns with precision and offer real-time feedback to both patients and therapists. By leveraging machine learning, AI systems can dynamically adapt rehabilitation protocols based on individual patient data collected from wearable sensors and other monitoring devices.
The goal of this special issue is to investigate the transformational influence of artificial intelligence (AI) on gait rehabilitation in order to improve therapeutic results for people who have mobility limitations due to accidents, surgeries, neurological diseases, or chronic illnesses. AI approaches enable exact analysis of complicated gait patterns and give real-time feedback to both patients and therapists, hence increasing the effectiveness of therapies. Using machine learning, AI systems may dynamically change rehabilitation regimens based on specific patient data from wearable sensors and other monitoring equipment. Finally, this special issue seeks to restore normal walking patterns, improve balance, avoid falls, and increase total functional ability, therefore greatly enhancing patients' quality of life.
This special issue, titled "Advancements in AI-Enhanced Gait Rehabilitation Techniques," aims to explore and highlight the latest developments, challenges, and future directions in the field of AI-driven gait rehabilitation. We invite researchers, clinicians, engineers, and industry professionals to contribute original research articles, review papers, case studies, and systematic reviews that advance our understanding and application of AI in enhancing gait rehabilitation.
Submissions may include, but are not limited to, the following topics:
1. Development and application of wearable sensors for real-time gait monitoring.
2. Predictive modelling for rehabilitation outcomes and patient progress.
3. AI-driven customization of rehabilitation protocols based on individual patient data.
4. AI-powered robotic exoskeletons and prosthetics that assist in gait training and rehabilitation.
5. Adaptive control systems in assistive devices for personalized support.
6. Utilization of VR and AR environments for immersive gait training experiences.
7. Development of AI-based tele-rehabilitation platforms for remote patient monitoring and intervention.
8. Real-world applications of AI-based gait rehabilitation techniques in various clinical settings.
9. Ethical issues surrounding the use of AI in gait rehabilitation, including patient privacy and data security.
Keywords:
Gait Analysis, Machine Learning, Biomechanics, Robotic Therapy, Rehabilitation Robotics
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.