How to convert emg signal to force

I have Emg signal of the right hand. What I want to know is it possible to find out the force that acted upon the muscle at that time interval.

Answer 1

[Star Strider]

That issue has been investigated extensively in the medical literature. (Search PubMed for details.)

It is not possible to infer the force generated by a muscle from an EMG signal. The EMG is an electrical phenomenon, force is a mechanical phenomenon, and they are only incidentally related. There are simply too many other variables involved, such as the biomechanics of the hand (in your example), and the force generated by each muscle fibre.

Answer 2

[Jan]

This is not a problem of Matlab, but a question concerning physiology. Therefore you ask in the wrong forum.

You can find a lot of corresponding papers. When you are working with skin electrodes, you will get large artifacts from the relative motion between the muscle and the skin. With fine-wire electrodes the accuracy will be higher, but the potential pain will influence the willingness of the persons to apply their full force. The total accuracy will be very limited, even for the large muscles on the leg. In some situations you cannot find a correlation at all.

Answer 3

[Hesan]

Hey,

You can check the relationship between force and EMG signals using the following methods:

1. Amplitude: An increase in force contraction leads to an increase in amplitude due to the recruitment of additional active motor units.
2. Mean Power Frequency: Similarly, an increase in force contraction also results in an increase in Mean Power Frequency.

However, you should consider fatigue, as it affects both amplitude and frequency.

If you want to understand why this occurs, here are some key points:

• The central nervous system can enhance muscle contraction strength through:
• Spatial recruitment: Increasing the number of active motor units, where amplitude represents the algebraic summation of several motor units.
• Temporal recruitment: Increasing the firing rate (firing frequency) of individual motor units to optimize the tension generated.

Additionally, there are several factors to consider regarding this relationship, such as electrode geometry, electrode placement, muscle fiber type, and more.