DescriptionThe dataset contains 3 sets of raw surface EMG signals recorded while performing pushups. The participant performed pushups till he could no longer continue. The three recordings were performed in 3 seperate instances seperated by sufficient time to allow for recovery. the numbering 1,2,3 is in temporal orderSignal DescriptionThe signal consists of 8 sEMG channels from Upper Trapezeus (Channel 0 and 1), triceps (Channel 2 and 6 ), Brachioradialis (Channel 3 and 4) and biceps ( channel 5 and 7) muscles. Each sensor channel records at a frequency of 1000Hz. All 8 channels are synchronised. Data FormatData is in the from of a list of JSON payloads each consisting of 200 data points each. Minimum Recomended data processing proceduresPre-Preperation --> Convert from JSON to DataFrameBand pass filter --> 20 - 450 HzNotch filter --> 50Hz (Power line frequency) Acknowledgement This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No's 101093069 (P2CODE) and 101120657(ENFIELD). Disclaimer: Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Commission. Neither the European Union nor the European Commission can be held responsible for them. Citation The users of this dataset are kindly asked to cite the following paper:Syed, D.A., Quadrini, W., Rahmani Choubeh, N., Pinzone, M., Gusmeroli, S. (2025). Approaching Interoperability and Data-Related Processing Issues in a Human-Centric Industrial Scenario. In: Presser, M., Skarmeta, A., Krco, S., González Vidal, A. (eds) Global Internet of Things and Edge Computing Summit. GIECS 2024. Communications in Computer and Information Science, vol 2328. Springer, Cham. https://doi.org/10.1007/978-3-031-78572-6_2