Freely available dataset of long-lasting surface electromyographic signals during walking

Abstract

It is acknowledged that surface electromyography (sEMG) signals vary from subject to subject and even within the same person [1]. In this scenario, it is important to analyze the natural variability associated with muscle activity during free walking to improve the interpretation of sEMG signals in both physiological and pathological conditions. Although few strides might be enough in some applications, the analysis of a larger number of gait cycles is highly recommended to analyze the variability of muscle recruitment during walking. However, free databases including long-lasting sEMG signals during walking are very uncommon to find. To fill this gap, the present study aims to introduce a database composed of long-lasting (around 5 minutes) surface EMG signals recorded from 2011 and 2018 during ground walking of 31 young able-bodied subjects. Synchronized basographic and electrogoniometric data are provided to allow users to achieve a spatial/temporal characterization of the sEMG signals. Basographic, electrogoniometric, and sEMG signals were acquired in a population of 31 young able- bodied subjects at Movement Analysis Lab, Università Politecnica delle Marche, Ancona, Italy. Inclusion criteria: 20 years < age < 30 years; 18.5 Kg/m 2 < body mass index, BMI < 25 Kg/m 2 . Subjects with pathological condition, joint pain, or undergone orthopedic surgery were excluded. All signals were recorded with a sampling rate of 2 kHz and a resolution of 12 bit by the multichannel recording system Step32, Medical Technology, Italy. Probes were applied over gastrocnemius lateralis (GL), tibialis anterior (TA), rectus femoris (RF), vastus lateralis (VL), and hamstrings (Ham) in both legs. Subjects have been asked to walk barefoot on level ground for around 5 min at their natural speed and pace, following an eight-shaped path which includes rectilinear segments and curves, including reversing, acceleration, and deceleration. The data base is composed of a total of 310 sEMG signals of average duration = 258 ± 53 s. Associated basographic and electrogoniometric data are provided. An example of a portion of basographic, electrogoniometric, and sEMG signals in a single stride is depicted in the following Fig. 1. Data are reported in function of gait cycle percentage. The considerable length of the signals makes this dataset very suitable for those studies where the numerosity of the data is essential, such as machine/deep learning approaches, studies for analyzing and quantifying the variability of muscle recruitment during physiological walking, creation of reference dataset in the characterization of pathological condition, and the validation of novel sEMG-based algorithms. This dataset is freely available, consulting the public repository of medical research data PhysioNet [2,3].