B. Lanzillo

G. D’Addio

L. Iuppariello

M. Cesarelli

M. Romano

N. Pappone

P. Bifulco

English

Archivio della ricerca - Università degli studi di Napoli Federico II

TITLE – EMG patterns of upper arm muscles during robotic rehabilitationL. Iuppariello (1), G. D’Addio (2), N. Pappone (2), B. Lanzillo (2), P. Bifulco (1), M. Romano(1), M.   Cesarelli (1)(1) Dept. of Electrical Engineering and Information Technology University of Naples, “Federico II”, Naples, Italy(2) S. Maugeri Foundation IRCCS, Telese Terme, ItalyMain topics: Human movement modelling and simulation in clinics; Clinical movement analysis of upper limb;INTRODUCTION and AIMChanges in muscle activation, underlying improvements in muscle strength and function in response to training of patients affected by congenital or acquired brain injury, remain to date poorly understood. It is thought that the mechanisms involved may be neural or muscular in origin. Better outcomes in sensorimotor as well as in cognitive processes are promised by emerging robot-mediated therapy (RMT), which allows quantitative kinematics and dynamics evaluations to estimate the patient’s progress. Although RMT have been differently applied for rehabilitation of patients affected by various diseases orthopaedic or neurological, at the best of our knowledge, no studies proposed a standardized quantitative electromyographic evaluation during robot assisted upper arm point-to-point movements. The aim of this paper is to describe the EMG patterns of upper arm muscles in 5 healthy subjects (HS) modelling the electromyographic linear envelope as summation of un-normalized Gaussian pulse.PATIENTS/MATERIALS and METHODSAll subjects were instrumented by wireless footswitches and surface EMG electrodes over medial deltoid(MD), brachial biceps(BB) brachial triceps(BT) AND sternal major pectoralis(SMP). The shoulder rehabilitation device used for this study was the Multi-Joint-System (in the following MJS) of the Tecnobody. The kinematic task required each subject to move from the center position to four target, equally spaced of 30°, and then return to the center with an 4 horizontal movements sequence: horizontal abduction of the right/left shoulder from the middle position to the outer right/left and return (RH1 and LH1 respectively), horizontal abduction of the right/left shoulder from the middle position to left/right external one and return (LH2 and RH2 respectively).EMG analysis has been performed by LEGLab, a software package specifically developed by authors which models the linear envelope (LE) of the EMG signal as summation of un-normalized Gaussian pulses of various length and amplitude, identifying the peak phase as the peak of the dominant component  having the highest amplitude. The position of the peak phase is expressed over the movement time duration (%). A physical significance of this dynamic index can be attributed to the phase involving a considerable underlying muscle effort while the peak of the LE, used increasingly for the assessment of normal and pathological muscle activity, gives information to the maximum strength developed in a short period.RESULTS and DISCUSSIONSThe purpose of this investigation has been to define  the EMG linear envelopes of  healthy individuals. This is accomplished by temporal feature extraction from LE's. The temporal feature extraction which converts a LE from gait EMG to a series of phases of activity has been developed modelling the LE as the summation of Gaussian pulses of various lengths. Results shown in the table shows mean and standard deviation of the peak phase position position for all studied muscle and for each movement.  In the figure is reported an example of the analysis on one muscle (SMP) over the RH1 movement duration (%). EMG LE represented with blue line and its peak with black star and the peak phase in green star.                   Table 1: mean ± standard deviation of the peak phase position                             for each muscle and for each movement	DM	BB	BT	SMPRH1	66.00 ± 8.90	75.00 ± 6.00	67.00 ± 10.00	29.00 ± 15.00LH1	24.00 ± 10.00	29.00 ± 7.00	57.00 ± 9.00 	37.00 ± 11.00LH2	61.00 ± 16.00	29.00 ± 19.00	61.00 ± 12.00	66.00 ± 6.20RH2	28.00 ± 11.00	66.00 ± 14.00	42.00 ± 11.00	55.00 ± 13.00This innovative approach have been shown to very effectively describe temporal EMG patterns, sharpening timing activations not directly observable by the simple LE usually available through commercial packages EMG Analysis. Knowledge and comprehension of EMG patterns is at the base of a correct clinical use of the rehabilitation device and of a quantitative evaluation of the rehabilitation outcomes, so the next step is to study the EMG pattern pathological subjects using the methodology described above in order to compare the position of the peak phase with respect to a normal pattern, and finally to study their variations during RMT.

EMG patterns of upper arm muscles during robotic rehabilitation

https://www.iris.unina.it/bitstream/11588/869506/1/CN21_Siamoc2014.doc

EMG patterns of upper arm muscles during robotic rehabilitation

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