Dataset for How muscle synergies fail to solve the muscle redundancy problem during human reaching

<b>Task</b><br>14 healthy right-handed participants (mean ± std age: 35.43 ± 17.62 years, 6 females 104 and 8 males) performed a modified center-out reaching task by pointing to visual targets in virtual reality. The center-out and return movements were repeated with each arm starting at one of two locations of the central target (lateral and medial), i.e., Llat and Rlat for reaches by left and right arm respectively in their respective lateral workspaces. EMG and kinematics were recorded and processed as described in Korol et al, 2024. <br><b>Dataset</b>The dataset consists of the principal component analysis of raw data for 10 adults and is saved in respective CSV files: DB_10sub_PC.csv; DB_10sub_VAF.csv; and DB_10sub_Score_EMG.csv. Additional 4 older adults are in the separate CSV files with similar organization (only Rlat and Llat): DB_4_older_sub_PC.csv; DB_4_older_sub_VAF.csv; and DB_4_older_sub_Score_EMG.csv. <b>Description</b><br><b>DB_10sub_PC</b><b>.csv</b> consists of the subject identifier (idSubject), starting hand location (sHand), and principal components (PCs) of EMG, active muscle torque, gravitational torque component, and dynamical torque component. Each is down-sampled to 100 samples (in columns).<b>DB_10sub_VAF</b><b>.csv</b> consists of the subject identifier (idSubject), starting hand location (sHand), PC identifier (idPC), and variance accounted for (VAF) of first 10 PCs of EMG, active muscle torque, gravitational torque component, and dynamical torque component (in columns).<br><b>DB_10sub_Score_EMG</b><b>.csv</b> consists of the subject identifier (idSubject), starting hand location (sHand), trial type identifier (idTrialType; 14 reaching directions forward and backward), muscle identifier (Muscle), and score values for 2 PCs of EMG (in columns).<br><br>