Table 3.
The identifier, title, and reference of the 65 selected primary studies (SPS) used in this SLR.
| ID SPS | Title | Type of Publication |
|---|---|---|
| SPS 1 | A Bionic Hand Controlled by Hand Gesture Recognition Based on Surface EMG Signals: A Preliminary Study [1] | Journal |
| SPS 2 | Real-Time Hand Gesture Recognition Based on Electromyographic Signals and Artificial Neural Networks [55] | Conference |
| SPS 3 | sEMG-Based Continuous Hand Gesture Recognition Using GMM-HMM and Threshold Model [56] | Conference |
| SPS 4 | Hand Gestures Recognition Using Machine Learning for Control of Multiple Quadrotors [57] | Symposium |
| SPS 5 | Real-Time Myocontrol of a Human–Computer Interface by Paretic Muscles After Stroke [58] | Journal |
| SPS 6 | Decoding of Individual Finger Movements From Surface EMG Signals Using Vector Autoregressive Hierarchical Hidden Markov Models (VARHHMM) [59] | Conference |
| SPS 7 | User-Independent Real-Time Hand Gesture Recognition Based on Surface Electromyography [60] | Conference |
| SPS 8 | Hand Gesture Recognition Using Machine Learning and the Myo Armband [61] | Conference |
| SPS 9 | Real-Time Hand Gesture Recognition Using the Myo Armband and Muscle Activity Detection [62] | Conference |
| SPS 10 | A Sub-10 mW Real-Time Implementation for EMG Hand Gesture Recognition Based on a Multi-Core Biomedical SoC [63] | Workshop |
| SPS 11 | Design and Myoelectric Control of an Anthropomorphic Prosthetic Hand [3] | Journal |
| SPS 12 | Wearable Armband for Real Time Hand Gesture Recognition [64] | Conference |
| SPS 13 | Simple Space-Domain Features for Low-Resolution sEMG Patternn Recognition [65] | Conference |
| SPS 14 | A Wireless Surface EMG Acquisition and Gesture Recognition System [66] | Congress |
| SPS 15 | Single Channel Surface EMG Control of Advanced Prosthetic Hands: A Simple, Low Cost and Efficient Approach [2] | Journal |
| SPS 16 | The Virtual Trackpad: an Electromyography-Based, Wireless, Real-Time, Low-Power, Embedded Hand Gesture Recognition System Using an Event-Driven Artificial Neural Network [67] | Journal |
| SPS 17 | Muscle-Gesture Robot Hand Control Based on sEMG Signals With Wavelet Transform Features and Neural Network classifier [68] | Conference |
| SPS 18 | Evaluating Sign Language Recognition Using the Myo Armband [69] | Symposium |
| SPS 19 | Spectral Collaborative Representation Based Classification for Hand Gestures Recognition on Electromyography Signals [70] | Conference |
| SPS 20 | A Convolutional Neural Network for Robotic Arm Guidance Using sEMG Based Frequency-Features [71] | Conference |
| SPS 21 | EMG Pattern Recognition Using Decomposition Techniques for Constructing Multiclass Classifier [72] | Conference |
| SPS 22 | SEMG Based Human Computer Interface for Physically Challenged Patients [73] | Conference |
| SPS 23 | EMG Feature Set Selection Through Linear Relationship for Grasp Recognition [74] | Journal |
| SPS 24 | A Portable Artificial Robotic Hand Controlled by EMG Signal Using ANN Classifier [75] | Conference |
| SPS 25 | Real-Time American Sign Language Recognition System by Using Surface EMG Signal [5] | Conference |
| SPS 26 | Hand Motion Recognition From Single Channel Surface EMG Using Wavelet & Artificial Neural Network [76] | Conference |
| SPS 27 | A Versatile Embedded Platform for EMG Acquisition and Gesture Recognition [77] | Journal |
| SPS 28 | Hybrid EMG classifier Based on HMM and SVM for Hand Gesture Recognition in Prosthetics [78] | Conference |
| SPS 29 | Human–Computer Interaction System Design Based on Surface EMG Signals [79] | Conference |
| SPS 30 | Towards EMG Control Interface for Smart Garments [80] | Symposium |
| SPS 31 | Identification of Low Level sEMG Signals for Individual Finger Prosthesis [81] | Conference |
| SPS 32 | Pattern Recognition of Eight Hand Motions Using Feature Extraction of Forearm EMG Signal [82] | Journal |
| SPS 33 | Pattern Recognition of Number Gestures Based on a Wireless Surface EMG System [83] | Journal |
| SPS 34 | Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning [84] | Journal |
| SPS 35 | Real-Time Hand Gesture Recognition Model Using Deep Learning Techniques and EMG Signals [85] | Conference |
| SPS 36 | Real-Time Hand Gesture Recognition Based on Artificial Feed-Forward Neural Networks and EMG [86] | Conference |
| SPS 37 | Pattern Recognition-Based Real Time Myoelectric System for Robotic Hand Control [87] | Conference |
| SPS 38 | Hand Gesture Recognition and Classification Technique in Real-Time [88] | Conference |
| SPS 39 | Forearm Muscle Synergy Reducing Dimension of the Feature Matrix in Hand Gesture Recognition [89] | Conference |
| SPS 40 | EMG Wrist-Hand Motion Recognition System for Real-Time Embedded Platform [90] | Conference |
| SPS 41 | Robust Real-Time Embedded EMG Recognition Framework Using Temporal Convolutional Networks on a Multicore IoT Processor [91] | Journal |
| SPS 42 | A Multi-Gestures Recognition System Based on Less sEMG Sensors [92] | Conference |
| SPS 43 | A Fully Embedded Adaptive Real-Time Hand Gesture Classifier Leveraging HD-sEMG & Deep Learning [93] | Journal |
| SPS 44 | Real-time Pattern Recognition for Hand Gesture Based on ANN and Surface EMG [94] | Conference |
| SPS 45 | Adjacent Features for High-Density EMG Pattern Recognition [95] | Conference |
| SPS 46 | Automatic EMG-based Hand Gesture Recognition System Using Time-Domain Descriptors and Fully-Connected Neural Networks [96] | Conference |
| SPS 47 | Artificial Neural Network to Detect Human Hand Gestures for a Robotic Arm Control [97] | Conference |
| SPS 48 | Electromyography-Based Hand Gesture Recognition System for Upper Limb Amputees [98] | Journal |
| SPS 49 | Robust Hand Gesture Recognition With a Double Channel Surface EMG Wearable Armband and SVM classifier [99] | Journal |
| SPS 50 | Fuzzy Classification of Hand’s Motion [100] | Conference |
| SPS 51 | EMG-Based Online Classification of Gestures With Recurrent Neural Networks [101] | Journal |
| SPS 52 | Teleoperated Robotic Arm Movement Using Electromyography Signal With Wearable Myo Armband [102] | Journal |
| SPS 53 | Identification of Gesture Based on Combination of Raw sEMG and sEMG Envelope Using Supervised Learning and Univariate Feature Selection [103] | Journal |
| SPS 54 | Surface EMG Hand Gesture Recognition System Based on PCA and GRNN [104] | Journal |
| SPS 55 | Dexterous Hand Gestures Recognition Based on Low-Density sEMG Signals for Upper-Limb Forearm amputees [105] | Journal |
| SPS 56 | Real-Time Surface EMG Pattern Recognition for Hand Gestures Based on an Artificial Neural Network [106] | Journal |
| SPS 57 | On the Usability of Intramuscular EMG for Prosthetic Control: A Fitts’ Law Approach [107] | Journal |
| SPS 58 | Validation of a Selective Ensemble-Based Classification Scheme for Myoelectric Control Using a Three-Dimensional Fitts’ Law Test [108] | Journal |
| SPS 59 | Support Vector Regression for Improved Real-Time, Simultaneous Myoelectric Control [109] | Journal |
| SPS 60 | Real-Time and Simultaneous Control of Artificial Limbs Based on Pattern Recognition Algorithms [110] | Journal |
| SPS 61 | On the Robustness of Real-Time Myoelectric Control Investigations: A Multiday Fitts’ Law approach [111] | Journal |
| SPS 62 | Regression Convolutional Neural Network for Improved Simultaneous EMG Control [112] | Journal |
| SPS 63 | A Comparison of the Real-Time Controllability of Pattern Recognition to Conventional Myoelectric Control for Discrete and Simultaneous Movements [31] | Journal |
| SPS 64 | A Real-Time Comparison Between Direct Control, Sequential Pattern Recognition Control and Simultaneous Pattern Recognition Control Using a Fitts’ Law Style Assessment Procedure [113] | Journal |
| SPS 65 | Evaluation of Computer-Based Target Achievement Tests for Myoelectric Control [46] | Journal |