Detection of Scoliosis

Early Detection of Adolescent Idiopathic Scoliosis Using Machine Learning on Plantar Pressure Data

This study aims to evaluate whether plantar pressure data collected during standing and walking can be used with machine learning to support early detection of scoliosis in young people. Patients with scoliosis and healthy volunteers aged 10-18 will undergo a short assessment using a pressure mat.

Inclusion Criteria:

• Healthy Controls: Adolescents without any spinal condition or significant musculoskeletal issues, and with no prior history of scoliosis, to provide normal plantar pressure data for comparison.
• Scoliosis Diagnosis: Adolescents diagnosed with adolescent idiopathic scoliosis (AIS) by a healthcare professional (through clinical evaluation and/or radiographic assessment) are eligible.
• Age: Participants must be between the ages of 10 and 18 years at the time of recruitment.
• Willingness to Participate: Participants and their parent(s)/guardian(s) must provide informed consent/assent prior to participation.
• Ability to Complete Study Procedures: Participants must be able to complete the plantar pressure measurement test, which requires standing on a pressure mat for a few minutes.

Exclusion Criteria

• Severe Pain or Discomfort: Participants unable to stand or walk comfortably due to pain or musculoskeletal issues.
• Non-cooperation: Participants who are unable or unwilling to follow instructions or consent/assent procedures.
• Uncontrolled Medical Conditions: Adolescents with uncontrolled conditions (e.g., cardiovascular or endocrine disorders) compromising participation.
• Recent Foot Injuries or Conditions: Participants with foot injuries or conditions (e.g., wounds, infections) that may interfere with plantar pressure measurement.