Development of a decision tool to optimize the orthotic design process
Recovery of balance and gait capacity is the primary aim in patients with neurological or muscular disorders to enhance daily functioning. Despite intensive training during rehabilitation, many patients remain with gait and balance impairments. To address these challenges, orthotics, like orthopedic shoes or orthoses, are commonly prescribed to further improve balance and gait in these patients. Determining the optimal orthotic solution relies on a comprehensive evaluation of patient characteristics and subjective observation of balance and gait problems by a multidisciplinary team consisting of a rehabilitation physician, orthotist, shoe technicians and physiotherapist. While instrumented gait analysis is an alternative, it is time consuming and expensive for routine clinical use.
In this collaborative effort involving Radboudumc, Sint Maartenskliniek and OIM orthopedie, we aimed to improve this process by using wearable sensor technology and videos in combination with artificial intelligence. To optimize the process, we developed a decision tree known as GaReC in three stages. In the initial stage, we defined the key mechanical characteristics of orthotics in relation the gait pattern. Furthermore, we assessed the impact of orthotics on the gait pattern and on the ability to response to adjustments in gait pattern. The second phase involved the development of a valid an reliable tool to objectively assess the most important biomechanical parameters for orthotic alignment. A sensor attached to the shank of a subject showed to be valid to assess the key biomechanical factor as defined in the initial phase. In addition, a video based assessment also demonstrated validity and reliability in assessing key biomechanical parameters for orthotic alignment. In the final phase, we evaluated the GareC’s potential in 30 people with orthotics, indicating that GaReC can effectively optimize the process of prescribing and evaluating orthotics
