5. Characteristics of Biosignals
ï§Often hidden in a background of other
signals and noise components.
ï§Generated by highly complex and dynamic
biological processes
with parameters
usually more than a few and varying
continuously
7. Biosignal Processing
In order to derive the required information from the
bio signals:
-Disturbance should be filtered out
-The amount of data should be reduced by
discriminating only the most significant ones
related with the required information
8. Stages of Biosignal Processing
ï§ Signal acquisition
ï§ Transformation and reduction of the
signals
ï§ Computation of signal parameters
that are diagnostically significant
ï§ Interpretation or classification of the
signals
9. Application of Biosignal Analysis
In ICUs
ï§ integrating signals from multiple sources
ï§ presenting information in the most appropriate form
ï§ interpreting variations over prolonged time periods
ï§ learning and recognizing profiles
ï§ triggering âintelligentâ alarms
10. Application Areas of Biosignal Analysis
ï§Biosignals offer parameters that support
medical decision making and trend
analysis.
ï§Bio signal analysis techniques help to
extract
these
parameters
accurately, analyze and interpret them
objectively.
12. Applications of EMG in Ergonomics
âș ANALYSIS OF DESIGN.
âș RISK PREVENTION.
âș ERGONOMIC DESIGN.
âș PRODUCT CERTIFICATION.
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13. Applications of EMG in Medical Research
âșEMG helps to improve
the medical research
studies by detecting
activity levels in muscles
and quickly identifying
muscle dysfunction.
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14. Applications of EMG in Medical Research
FUNCTIONAL NEUROLOGY
GAIT AND POSTURE ANALYSIS
PROSTHETIC DEVICES
ORTHOPEDICS
SURGERY
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15. EMG For A Robotic Hand
ïFigure shows the highly
integrated approach to use
EMG recording of the
human lower arm in order
to control the opening and
closing of three fingers of
the hand.
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16. Applications of EMG in Sports Science
âș Biomechanics is the
scientific study of forces
and the effects of those
forces on and within the
human body.
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