An Easy-to-Use Assessment System for Spasticity Severity Quantification in Post-Stroke Rehabilitation

Spasticity is a motor disorder integrated in the upper motor neuron syndrome resulting from central nerve diseases such as stroke. The multifactorial nature of spasticity manifestations leads to the inter-rater and intrarater reliability of clinical assessment, hence, the objective severity quantification of the spastic hypertonia has attracted significant attention in the context of post-stroke rehabilitation. Here, we developed a novel assessment system to reliably identify the exaggerated muscle tone and quantitatively estimate the symptom severity in patients with upper limb spasticity. Twenty subjects with post-stroke spasticity (53.0 ± 13.9 years old) and ten age-matched healthy subjects performed the passive stretch movements under the single-task and dual-task protocols while wearing an exoskeletal measurement device developed by us. A preliminary identification layer was designed to discriminate the pathological electrophysiological outputs of the upper extremity muscles by using the long short-term memory (LSTM) networks. In the next layer, the severity quantification models can be triggered in parallel, aiming at evaluating the neural and non-neural level pathologies underlying the spastic resistance manually percepted by clinicians, where the muscle activation/co-activation features, kinematic departure, and biomechanical characteristics were considered to improve the clinical relevance. Based on these single-level decisions, the third layer was constructed as an integrated model to yield a more comprehensive quantification of the symptom severity. The experimental validation of the proposed system demonstrated good reliability in discriminating the spastic hypertonia from the normal muscle tone, as well as strong agreement of the quantitative severity estimations with the commonly accepted clinical scales for the neural level
${(R = 0.79,\;P = 2.79e - 5)}$
, non-neural level
${(R = 0.75,\;P = 1.62e - 4)}$
, and integrated level
${(R = 0.86,\;P = 9.86e - 7)}$
. In conclusion, the proposed assessment system holds great promise to provide clinicians with an easy-to-use tool as suitable support for spasticity diagnosis, disease monitoring, and treatment adjustment.