Aim: The first aim of this study was to systematically review and critically assess manually controlled instrumented spasticity assessment methods that combine multidimensional signals. The second aim was to extract a set of quantified parameters that are psychometrically sound to assess spasticity in a clinical setting. Method: Electronic databases were searched to identify studies that assessed spasticity by simultaneously collecting electrophysiological and biomechanical signals during manually controlled passive muscle stretches. Two independent reviewers critically assessed the methodological quality of the psychometric properties of the included studies using the COSMIN guidelines. Results: Fifteen studies with instrumented spasticity assessments met all inclusion criteria. Parameters that integrated electrophysiological signals with joint movement characteristics were best able to quantify spasticity. There were conflicting results regarding biomechanical-based parameters that quantify the resistance to passive stretch. Few methods have been assessed for all psychometric properties. In particular, further information on absolute reliability and responsiveness for more muscles is needed. Interpretation: Further research is required to determine the correct parameters for quantifying spasticity based on integration of signals, which especially focuses on distinguishing the neural from non-neural contributions to increased joint torque. These parameters should undergo more rigorous exploration to establish their psychometric properties for use in a clinical environment.