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Synchronization of EMG and GRF Measurement System Using LabVIEW and Matlab Tools

Synchronization of EMG and GRF Measurement System Using LabVIEW and Matlab Tools. Moulali.P Central Scientific Instruments Organization (CSIO), Council for Scientific and Industrial Research (CSIR), Chandigarh, India. Overview. Introduction EMG VGRF Objective Methods & Materials

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Synchronization of EMG and GRF Measurement System Using LabVIEW and Matlab Tools

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  1. Synchronization of EMG and GRF Measurement System Using LabVIEW and Matlab Tools Moulali.P Central Scientific Instruments Organization (CSIO), Council for Scientific and Industrial Research (CSIR), Chandigarh, India.

  2. Overview • Introduction • EMG • VGRF • Objective • Methods & Materials • Experimental set-up for data acquisition • Software Analysis • LabVIEW VI for data acquisition • Matlab Analysis • Results and Discussion • Conclusions • Future Work • References

  3. 1. INTRODUCTION Raw EMG signal • EMG -Electromyography : study of muscle function through analysis of electrical signals emanated during muscular contraction. • VGRF-Vertical Ground Reaction Force: vertical component of force exerted on foot by the ground during walking. Amplitude (mv) Time(ms) Fz1 Fz3 Fz2

  4. Four active EMG surface electrodes attached to right leg of subject over • gastrocnemius lateralis (GL) • tibialis anterior (TA) • biceps femoris (BF) • vastuslateralis (VL) Biometrics SX230 active surface electrode

  5. Objective Synchronizing EMG and VGRF data using LabVIEW software and analyzing the LabVIEW data with Matlab tool box. • Hardware and software development for acquisition of EMG and force plate data (VGRF) at a time. Applications: • Displaying synchronized data in one panel side by side. • Acquired (synchronized) data provides comparison of VGRF & EMG data simultaneously.

  6. Materials & Methods Experimental set-up

  7. Subject with EMG electrodes walking over the Kistler force plate

  8. LabVIEW VI for data acquisition • Synchronized data is acquired and stored in computer for further analysis • EMG data acquired directly and low pass filters used before acquiring GRF data Block diagram of VI for synchronization of both EMG and force plate data.

  9. Matlab Analysis • Obtained data from LabVIEW is imported into Matlab tool for analysis. • It is observed that there is DC offset error in the raw EMG signal but no such effect is observed in in force signal. • Next the signal is rectified and passed through low pass filter and notch filter. • RMS, Mean and Median are calculated • From VGRF peak values are calculated by writing separate Matlab code

  10. Raw EMG Signal Elimination of DC Offset Rectification Low Pass Filtered Signal Notch Filtered Signal Time Domain Frequency domain Mean Median RMS Flow chart showing steps involved in EMG signal analysis

  11. Results and Discussion • To show results MATLAB Graphical User Interface (GUI) was developed. • Using GUI , synchronized data was loaded into the program and the required parameters of EMG and force data were evaluated.

  12. Developed GUI for analysis of synchronized EMG and force data

  13. Conclusion • Analyzed data helps us to understand how GRF have stimulated the muscle activity. • Results obtained from analyzing module are exactly not matching to those obtained from the software that are provided along with those system. It is because the techniques used for analysis is not alike or some multiplication factor missing .

  14. Future scope • Analysis module is in developing stage , so we are trying to incorporate a number of other parameters, which will enhance the performance of developed tool. • The parameter values are to be cross verified with standard reference tool.

  15. References [1]. Q.H Huang, Y.P Zheng, X.Chena, J.F He and J Shi (2007). A system for the synchronized recording of sonomyography, electromyography and joint angle. Open Biomed Eng J.2007; 1: (77-84). [2]. Finch.A.E, Ariel G.A, and Penny A.M , Biomechanical integration of essential human movement parameters. [3]. Levin.O, Mizrahil.J, Adam.D, Verbitsky.O and Isakov.E.(). On the correlation between force plate data and EMG in various standing conditions. [4]. Sousa.F, Conceiltao.F, Gonltalyes.P, Carvalho.J.M, Soares.DScarrone.F, Loss.J, Vilas-Boas.J.P(2002). Biomechanical analysis of elementary ballet jumps; Integration of force plate data and EMG records. ISBS 2002, Caceres-Extremadura-Spain(175-178).

  16. THANK YOU

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