1. ELECTROMYOGRAM Amit Sethi Pre-doc Rehab Sciences, MS OTR/L

2. INTRODUCTION Electromyogram (EMG) is a technique for evaluating and recording the activation signal of muscles. EMG is performed by an electromyograph, which records an electromyogram. Electromyograph detects the electrical potential generated by muscle cells when these cells contract and relax.

3. INTRODUCTION Contd. EMG ApparatusMuscle Structure/EMG

4. ELECTRICAL CHARACTERITICS The electrical source is the muscle membrane potential of about -70mV. Measured EMG potentials range between < 50 μV up to 20 to 30 mV, depending on the muscle under observation. Typical repetition rate of muscle unit firing is about 7-20 Hz. Damage to motor units can be expected at ranges between 450 and 780 mV

5. ELECTRODE TYPES Intramuscular - Needle Electrodes Extramuscular - Surface Electrodes

6. EMG PROCEDURE Clean the site of application of electrode; Insert needle/place surface electrodes at muscle belly; Record muscle activity at rest; Record muscle activity upon voluntary contraction of the muscle.

7. EMG Contd. Muscle Signals are Analog in nature. EMG signals are also collected over a specific period of time. Analog Signal

8. EMG Contd. EMG processing: Amplification & Filtering Signal pick up Conversion of Analog signals to Digital signals Computer

9. APPLICATION OF EMG EMG can be used for diagnosis of Neurogenic or Myogenic Diseases. You tube link of EMG

10. SAMPLE EMG DATA

11. BIOMECHANICS Biomechanics is the research and analysis of the mechanics of living organisms. mechanicsorganisms KINEMATICS – The branch of Biomechanics concerned with describing the motion of bodies. KINETICS- The branch of biomechanics concerned with explaining the causes of body motions.

12. KINEMATICS Contd.  Data is usually collected with Motion Capture Devices over a specific time period.  VICON  Motion Analysis Corporation  Qualysis Typical Set up of Motion Analysis Lab

13. SAMPLE KINEMATIC DATA

16. KINEMATICS DATA ANALYSIS Aim: to identify the variability in reaching movement in normal and stroke individuals. Outcome Variable: Elbow Joint Angle. Magnitude of variability was analyzed with Std. Deviation. Structure of variability in elbow angles was computed via IE using MATLAB. H = Log2 (1/Pi) Pi = probability that a given event will occur. Pi α1/H. Higher values of IE suggest - more uncertainty. Lower values of IE suggest- less uncertainty (increased stability). of

17. RESULTS SubjectSD PreSD PostIE PreIE Post 1 4.54 1.80 0.58 0.80 2 3.69 2.67 0.79 0.50 Control SD = 2.68IE = 2.33

18. CONCLUSION Variability/Uncertainity in movement is higher in normals as compared to individuals with Stroke. This variability could be correlated with adaptability in movement which is decreased upon nervous system damage in Stroke. Large data is required to generalize these results.