Continuous similarity analysis in patient populations

Decreased movement symmetry is associated with injury risk and accelerated disease progression. Methods to analyze continuous data either cannot be used in pathologic populations with abnormal movement patterns or are not defined in terms easily incorporated into clinical care. The purpose of this study was to develop a method of describing symmetry and movement quality in continuous time-series data that results in scores that can be readily incorporated into clinical care. Two scores were developed: (1) the symmetry score (SS) which evaluates similarities in time-series data between limbs and (2) the closeness-to-healthy score (CTHS) which evaluates the similarity of time-series data to a control population. Kinetic and kinematic data from 56 end-stage unilateral ankle arthritis (A-OA) patients and 56 healthy older adults, along with 16 anterior cruciate ligament reconstruction (ACLR) patients and 16 healthy young adults were used to test the ability for SS and CTHS to differentiate between healthy and patient groups. Unpaired t-tests, Cohen’s D effect sizes, and receiver-operating-curve analyses assessed group differences [SPSS, V27, α = 0.05]. Patients had worse SS than controls and A-OA patients had worse CTHS compared to controls. SS had strong predictive capability, while the predictive capability of CTHS varied. Combined with clinically accessible data collection methods, the SS and CTHS could be used to evaluate patients’ baseline movement quality, assess changes due to disease progression, and during recovery. Results could be utilized in clinical decision making to assess surgical intervention urgency and efficacy of surgical interventions or rehabilitation protocols to improve side-to-side limb symmetry.