The Muscle Load Analysis add-on is designed for online (during the acquisition) and offline (post-processing) evaluation of muscular load in ergonomics, biomechanics, and sports research applications, and is the ideal software extension for PLUX Electromyography (EMG) sensors.
It measures the muscular load that muscles are subjected during a period or task (e.g. during a normal work day or work process) according to Jonsson’s method of Amplitude Probability Distribution Analysis (APDA) of acquired EMG signals. For this method, the Maximum Voluntary Contraction (MVC) of the monitored muscle is acquired before the acquisition and used as reference value for the muscle load classification in static, median, and high intensity levels.
Supported Sensors
- BITalino Electromyography (EMG)
- biosignalsplux Electromyography (EMG)
- biosignalsplux muscleBAN
Included in the following kits
Specifications
The Muscle Load Analysis add-on measures the muscular load that muscles are subjected during a period or task (e.g. during a normal work day or work process) according to Jonsson’s method of Amplitude Probability Distribution Analysis (APDA) of acquired EMG signals. For this method, the Maximum Voluntary Contraction (MVC) of the monitored muscle is acquired before the acquisition and used as reference value for the muscle load classification in static, median, and high intensity levels.
The APDA calculates the cumulative percentage histogram of the enveloped data in terms (%) of the MVC. The development of the APDA can be observed in OpenSignals when acquiring EMG signal in real-time enabling intervention possibilities whenever a subject is reaching levels of muscle tiredness (orange Warning Zone) or even fatigue (orange Danger Zone).
Tiredness Zone
Tired out muscles can be damaged, causing pain to the subject, reason for which tiredness should be avoided.
Fatigue Evaluation
High intensity muscular load causes the muscles to fail producing the required force for a task, which can lead to severe Musculoskeletal Disorders when the continuous fatigue outbalances the body’s natural recovery mechanism’s.
Downloads
You can use the following sample data to test the add-on yourself (a free version of the add-on is included in the free OpenSignals base version):
You can download sample reports of this add-on here (PDF):
