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Hi,
I am a research student undertaking a combined physiological and
biomechanical study which I am currently writing up. The topic is an
investigation into the effects of Hypoxic and Hyperoxic conditions on a
variety of measures, including EMG. The study used 10 subjects who
exercised on an arm-crank ergometer using an incremental step design to
exhaustion. The workload was increased every 4 minutes and on average
each subject completed 4 workloads. One of my reasons for doing this
study is based on a paper by Kayser (1994) who used iEMG - therefore I
have used the same measure. I collected EMG from the Biceps, Triceps and
Anterior Deltoid muscles.
I collected EMG continuously during the data collection from each
subject and then used the following method to arrive at an iEMG value
for each workload:
-slice off the final 30s of EMG data (the rationale being the subject
would be in physiological "steady state")
-use the DC offset function to remove equipment noise.
-RMS the filtered data.
-Integrate the RMS data.
I was wondering if Biomch-L subscribers could comment on my EMG signal
analysis as to whether they think I have used the correct methodology or
if there is a better method I may be able to use. I have all the EMG
data saved and access to EMGWorks.
Thanks very much,
Graham Mytton
University of Sunderland.
I am a research student undertaking a combined physiological and
biomechanical study which I am currently writing up. The topic is an
investigation into the effects of Hypoxic and Hyperoxic conditions on a
variety of measures, including EMG. The study used 10 subjects who
exercised on an arm-crank ergometer using an incremental step design to
exhaustion. The workload was increased every 4 minutes and on average
each subject completed 4 workloads. One of my reasons for doing this
study is based on a paper by Kayser (1994) who used iEMG - therefore I
have used the same measure. I collected EMG from the Biceps, Triceps and
Anterior Deltoid muscles.
I collected EMG continuously during the data collection from each
subject and then used the following method to arrive at an iEMG value
for each workload:
-slice off the final 30s of EMG data (the rationale being the subject
would be in physiological "steady state")
-use the DC offset function to remove equipment noise.
-RMS the filtered data.
-Integrate the RMS data.
I was wondering if Biomch-L subscribers could comment on my EMG signal
analysis as to whether they think I have used the correct methodology or
if there is a better method I may be able to use. I have all the EMG
data saved and access to EMGWorks.
Thanks very much,
Graham Mytton
University of Sunderland.