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Upper extremity motor impairment affects about 80\% of persons after strokes.For stroke rehabilitation, upper limb kinematic assessments have increasinglybeen used as primary or secondary outcome measures. Studying the upperextremity provides a valuable tool for assessing limb coordination,mal-adaptations, and recovery. There is currently no universal standardizedscale for categorizing multi-joint upper extremity movement. We propose amodified Procrustes statistical shape method as a quantitative analysis thatcan recognize segments of movement where multiple limb segments arecoordinating movement. Generalized Procrustes methods allow data points to becompared across an array simultaneously rather than comparing them in pairs.Rather than rely solely on discrete kinematic values to contrast movement, thismethod allows evaluation of how movement progresses. The Procrustes analysis ofable-bodied movement showed that the hand and forearm segments moved in a morecoordinated manner during initiation. The shoulder and elbow become morecoordinated during movement completion. In impaired movement, this coordinationbetween the hand and forearm is disrupted. Potentially mal-adaptivecompensation occurs between the upper arm and forearm after movement enters thedeceleration phase. The utilization of Procrustes analysis may be a steptowards developing a comprehensive and universal quantitative tool that doesnot require changes to existing treatments or increase patient burden.  Copyright 2023 IEEE. Personal use of this material is permitted. Permissionfrom IEEE must be obtained for all other uses, in any current or future media,including reprinting/republishing this material for advertising or promotionalpurposes, creating new collective works, for resale or redistribution toservers or lists, or reuse of any copyrighted component of this work in otherworks.

A Novel Procrustes Analysis Method to Quantify Multi-Joint Coordination of the Upper Extremity after Stroke