Research Topic

Diagnosis of Human Pathologies Using Computational Intelligence Techniques and Robotic Rehabilitation

About this Research Topic

The diagnosis of human pathologies, including Parkinson’s and human gait disorders, using computational intelligence techniques is one of the most active research fields in biomedical engineering. Diagnosis, being the first step in medical practice, is very crucial for clinical decision-making. Clinical pathology analysis methods aim to provide an objective to quantify the severity of the pathology. More recently, changes are taking place whereby a set of pathology-related disorders are identified and can be used to support diagnosis and the development of new robotic assistive technologies. Rehabilitation robotics includes the development of robotic devices tailored for assisting different sensorimotor functions (e.g. arm, hand, leg, ankle), development of different schemes of assistive therapeutic training, and assessment of sensorimotor performance (ability to move) of the patient; here, robots are used mainly as therapy aids instead of assistive devices.

The goal of this Research Topic is to focus on the intersection of neuroscience physical diagnosis technologies. The aim is to provide new intelligent approaches and robotics technologies for better understanding the intelligent systems applications, human diseases, and the relationships between them, with a focus on intelligent diagnosis and robotic rehabilitation. Present-generation rehabilitation robots are designed as complements, rather than substitutes, of the therapist's work. They support the recovery of functions by efficiently exploiting the structure and adaptive properties of the human sensorimotor systems and provide rich information on sensorimotor performance and their evolution. Their design, implementation, and modalities of intervention incorporate findings from behavioral studies on sensorimotor adaptation and motor skill learning and their neural substrates.

Submissions to this Research Topic on “Diagnosis of Human Pathologies Using Computational Intelligence Techniques and Robotic Rehabilitation” are solicited to represent a snapshot of the field’s development by covering a range of topics that include but are not limited to new systems, algorithms, solutions, and applications in the following areas:

• Human gait and balance analysis
• Diagnosis of gait disorders
• Neuroscience physical diagnosis
• Robotic rehabilitation
• Other human diseases diagnosis.


Keywords: Diagnosis of Gait Disorders, Neuroscience Physical Diagnosis, Robotic Rehabilitation, Human Pathologies Diagnosis, Computational Intelligence


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.

The diagnosis of human pathologies, including Parkinson’s and human gait disorders, using computational intelligence techniques is one of the most active research fields in biomedical engineering. Diagnosis, being the first step in medical practice, is very crucial for clinical decision-making. Clinical pathology analysis methods aim to provide an objective to quantify the severity of the pathology. More recently, changes are taking place whereby a set of pathology-related disorders are identified and can be used to support diagnosis and the development of new robotic assistive technologies. Rehabilitation robotics includes the development of robotic devices tailored for assisting different sensorimotor functions (e.g. arm, hand, leg, ankle), development of different schemes of assistive therapeutic training, and assessment of sensorimotor performance (ability to move) of the patient; here, robots are used mainly as therapy aids instead of assistive devices.

The goal of this Research Topic is to focus on the intersection of neuroscience physical diagnosis technologies. The aim is to provide new intelligent approaches and robotics technologies for better understanding the intelligent systems applications, human diseases, and the relationships between them, with a focus on intelligent diagnosis and robotic rehabilitation. Present-generation rehabilitation robots are designed as complements, rather than substitutes, of the therapist's work. They support the recovery of functions by efficiently exploiting the structure and adaptive properties of the human sensorimotor systems and provide rich information on sensorimotor performance and their evolution. Their design, implementation, and modalities of intervention incorporate findings from behavioral studies on sensorimotor adaptation and motor skill learning and their neural substrates.

Submissions to this Research Topic on “Diagnosis of Human Pathologies Using Computational Intelligence Techniques and Robotic Rehabilitation” are solicited to represent a snapshot of the field’s development by covering a range of topics that include but are not limited to new systems, algorithms, solutions, and applications in the following areas:

• Human gait and balance analysis
• Diagnosis of gait disorders
• Neuroscience physical diagnosis
• Robotic rehabilitation
• Other human diseases diagnosis.


Keywords: Diagnosis of Gait Disorders, Neuroscience Physical Diagnosis, Robotic Rehabilitation, Human Pathologies Diagnosis, Computational Intelligence


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.

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Submission Deadlines

21 January 2022 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

21 January 2022 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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