Spasticity Measurement Based on the HHT Marginal Spectrum Entropy of sEMG Using a Portable System: A Preliminary Study

To facilitate stretch reflex onset (SRO) detection and improve accuracy and reliability of spasticity assessment in clinical settings, a new method to measure dynamic stretch reflex threshold (DSRT) based on Hilbert–Huang transform marginal spectrum entropy (HMSEN) of surface electromyography (sEMG) signals and a portable system to quantify modified Ashworth scale (MAS) for spasticity assessment were developed. The sEMG signals were divided into frames using a fixed-length sliding window, and the HMSEN of each frame was calculated. An adaptive threshold was set to measure the DSRT. The HMSEN based method can quantify muscle activity through time-frequency and nonlinear dynamics analysis, therefore providing deeper insight about the spastic muscle mechanisms during stretching and a reliable SRO detection method. Experimental results revealed that the HMSEN based method could reliably detect the SRO and measure the DSRT (recognition rate: 95.45%), and could achieve improved performance over the time-domain based method. There was a strong correlation ( ${r} = -0.824$ to −0.900) between the MAS scores and the DSRT index, and the test-retest reliability was high. Additionally, limitations of the MAS were analyzed. This paper indicates that the presented framework can provide a promising tool to measure DSRT and a clinical quantitative approach for spasticity assessment.

[1]  Allison M. Okamura,et al.  Haptic Simulation of Elbow Joint Spasticity , 2008, 2008 Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems.

[2]  Winnie Ka Ling Yam,et al.  Interrater Reliability of Modified Ashworth Scale and Modified Tardieu Scale in Children With Spastic Cerebral Palsy , 2006, Journal of child neurology.

[3]  C. McGibbon,et al.  Elbow spasticity during passive stretch-reflex: clinical evaluation using a wearable sensor system , 2013, Journal of NeuroEngineering and Rehabilitation.

[4]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[5]  Katrijn Klingels,et al.  Upper limb motor and sensory impairments in children with hemiplegic cerebral palsy. Can they be measured reliably? , 2010, Disability and rehabilitation.

[6]  F. Mohd-Yasin,et al.  Techniques of EMG signal analysis: detection, processing, classification and applications , 2006, Biological Procedures Online.

[7]  J. Gaugler,et al.  Spasticity over time during acute rehabilitation: a study of patient and clinician scores. , 2016, Applied nursing research : ANR.

[8]  Junji Furusho,et al.  Leg-Robot for Demonstration of Spastic Movements of Brain-Injured Patients with Compact Magnetorheological Fluid Clutch , 2010, Adv. Robotics.

[9]  Chou-Ching K. Lin,et al.  Time-course analysis of stretch reflexes in hemiparetic subjects using an on-line spasticity measurement system. , 2000, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[10]  Josien C van den Noort,et al.  Evaluation of clinical spasticity assessment in cerebral palsy using inertial sensors. , 2009, Gait & posture.

[11]  H Rodgers,et al.  A review of the properties and limitations of the Ashworth and modified Ashworth Scales as measures of spasticity , 1999, Clinical rehabilitation.

[12]  K. Sakamoto,et al.  Chaotic analysis of electromyography signal at low back and lower limb muscles during forward bending posture. , 2005, Electromyography and clinical neurophysiology.

[13]  Hyung-Soon Park,et al.  Accuracy and reliability of haptic spasticity assessment using HESS (Haptic Elbow Spasticity Simulator) , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[14]  James W. Lance,et al.  The control of muscle tone, reflexes, and movement , 1980, Neurology.

[15]  Laura Mori,et al.  Pathophysiology of Spasticity: Implications for Neurorehabilitation , 2014, BioMed research international.

[16]  U. Rajendra Acharya,et al.  Application of entropies for automated diagnosis of epilepsy using EEG signals: A review , 2015, Knowl. Based Syst..

[17]  The relationship between isokinetic muscle strength and spasticity in the lower limbs of stroke patients. , 2015, Journal of bodywork and movement therapies.

[18]  Takashi Komeda,et al.  Development of an upper limb patient simulator for physical therapy exercise , 2011, 2011 IEEE International Conference on Rehabilitation Robotics.

[19]  A. Jahangir,et al.  Intramuscular injection of botulinum toxin for the treatment of wrist and finger spasticity after stroke. , 2007, The Medical journal of Malaysia.

[20]  D.M. Mount,et al.  An Efficient k-Means Clustering Algorithm: Analysis and Implementation , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  M. Stokes,et al.  Reliability of assessment tools in rehabilitation: an illustration of appropriate statistical analyses , 1998, Clinical rehabilitation.

[22]  K Desloovere,et al.  A clinical measurement to quantify spasticity in children with cerebral palsy by integration of multidimensional signals. , 2013, Gait & posture.

[23]  Diane L Damiano,et al.  What does the Ashworth scale really measure and are instrumented measures more valid and precise? , 2002, Developmental medicine and child neurology.

[24]  Hong-Bo Xie,et al.  Measuring time series regularity using nonlinear similarity-based sample entropy , 2008 .

[25]  Dara Meldrum,et al.  Reliability of surface electromyography timing parameters in gait in cervical spondylotic myelopathy. , 2011, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[26]  Yasuhiro Akiyama,et al.  Wearable dummy to simulate joint impairment: severity-based assessment of simulated spasticity of knee joint , 2013, Proceedings of the 2013 IEEE/SICE International Symposium on System Integration.

[27]  AD Pandyan,et al.  Spasticity: Clinical perceptions, neurological realities and meaningful measurement , 2005, Disability and rehabilitation.

[28]  Chen Jua An Onset Detection Method for Action Surface Electromyography Based on Sample Entropy , 2016 .

[29]  Eduardo Palermo,et al.  Spasticity Measurement Based on Tonic Stretch Reflex Threshold in Children with Cerebral Palsy Using the PediAnklebot , 2017, Front. Hum. Neurosci..

[30]  Ping Zhou,et al.  Sample entropy analysis of surface EMG for improved muscle activity onset detection against spurious background spikes. , 2012, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[31]  J M Bland,et al.  Statistical methods for assessing agreement between two methods of clinical measurement , 1986 .

[32]  Hyung-Soon Park,et al.  Quantitative evaluations of ankle spasticity and stiffness in neurological disorders using manual spasticity evaluator. , 2011, Journal of rehabilitation research and development.

[33]  Jie Liu,et al.  EMG burst presence probability: a joint time-frequency representation of muscle activity and its application to onset detection. , 2015, Journal of biomechanics.

[34]  Fabrizio Pisano,et al.  Quantitative measures of spasticity in post-stroke patients , 2000, Clinical Neurophysiology.

[35]  Anatol G. Feldman,et al.  Spasticity measurement based on tonic stretch reflex threshold in stroke using a portable device , 2008, Clinical Neurophysiology.

[36]  V Reggie Edgerton,et al.  Spasticity: a switch from inhibition to excitation , 2010, Nature Medicine.

[37]  Y. Wang,et al.  A dynamic neuromuscular model for describing the pendulum test of spasticity , 1997, IEEE Transactions on Biomedical Engineering.

[38]  Anatol G. Feldman,et al.  Stretch-reflex threshold modulation during active elbow movements in post-stroke survivors with spasticity , 2017, Clinical Neurophysiology.

[39]  Pierre A. Mathieu,et al.  Relationship between stretch reflex thresholds and voluntary arm muscle activation in patients with spasticity , 2007, Experimental Brain Research.

[40]  J. Weir Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. , 2005, Journal of strength and conditioning research.

[41]  J. Mehrholz,et al.  The influence of contractures and variation in measurement stretching velocity on the reliability of the Modified Ashworth Scale in patients with severe brain injury , 2005, Clinical rehabilitation.

[42]  J. Fleiss,et al.  Intraclass correlations: uses in assessing rater reliability. , 1979, Psychological bulletin.

[43]  Po-Lei Lee,et al.  Quantifying Spasticity With Limited Swinging Cycles Using Pendulum Test Based on Phase Amplitude Coupling , 2016, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[44]  J S Rietman,et al.  Stop using the Ashworth Scale for the assessment of spasticity , 2009, Journal of Neurology, Neurosurgery & Psychiatry.

[45]  Chul-Gyu Song,et al.  Portable measurement system for the objective evaluation of the spasticity of hemiplegic patients based on the tonic stretch reflex threshold. , 2011, Medical engineering & physics.

[46]  Hyung-Soon Park,et al.  Development of a Haptic Elbow Spasticity Simulator (HESS) for Improving Accuracy and Reliability of Clinical Assessment of Spasticity , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[47]  Mindy F Levin,et al.  Tonic Stretch Reflex Threshold as a Measure of Spasticity: Implications for Clinical Practice , 2009, Topics in stroke rehabilitation.