UPRAVLJANJE SA VIŠE STEPENI SLOBODE PRIMENOM TEHNIKA MAŠINSKOG UČENJA
Ključne reči:
Mioelektrične proteze, Prepoznavanje obrazaca, Mašinsko učenje, LDA, SVM, ANN
Apstrakt
U ovom radu predstavljeno je upravljanje mioelektričnom protezom šake koje podrazumeva klasifikaciju 9 pokreta šake na osnovu ulaznih EMG signala zabeleženih sa četiri mišića podlaktice. Klasifikacioni algoritmi mašinskog učenja koji su razmatrani u ovom radu su LDA, SVM i ANN. Mere uspešnosti upotrebljene u cilju analize performansi klasifikatora su tačnost, osetljivost, specifičnost i preciznost.
Reference
[1] F. Mereu, F. Leone, C. Gentile, F. Cordella, E. Gruppioni, and L. Zollo, “Control Strategies and Performance Assessment of Upper-Limb TMR Prostheses: A Review,” Sensors, Vol. 21, no. 6, p. 1953, Mar. 2021.
[2] A. Marinelli et al., “Active upper limb prostheses: a review on current state and upcoming breakthroughs”, Progress in Biomedical Engineering, Vol. 5, no. 1, p. 012001, Jan. 2023.
[3] M. Legrand, “Upper limb prostheses control based on user’s body compensations,” theses.hal.science, Mar. 2021.
[4] M. Hakonen, H. Piitulainen, and A. Visala, “Current state of digital signal processing in myoelectric interfaces and related applications,” Biomedical Signal Processing and Control, Vol. 18, pp. 334–359, Apr. 2015.
[5] G. Li, “Electromyography Pattern-Recognition-Based Control of Powered Multifunctional Upper-Limb Prostheses,” Advances in Applied Electromyography, Aug. 2011.
[6] Tijana Nosek, Branko Brkljač, Danica Despotović, Milan Sečujski, Tatjana Lončar-Turukalo, “Praktikum iz mašinskog učenja”, Univerzitet u Novom Sadu, 2020.
[7] Yang, Li, and Abdallah Shami. “On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice.” Neurocomputing, Vol. 415, pp. 295–316, Nov. 2020.
[2] A. Marinelli et al., “Active upper limb prostheses: a review on current state and upcoming breakthroughs”, Progress in Biomedical Engineering, Vol. 5, no. 1, p. 012001, Jan. 2023.
[3] M. Legrand, “Upper limb prostheses control based on user’s body compensations,” theses.hal.science, Mar. 2021.
[4] M. Hakonen, H. Piitulainen, and A. Visala, “Current state of digital signal processing in myoelectric interfaces and related applications,” Biomedical Signal Processing and Control, Vol. 18, pp. 334–359, Apr. 2015.
[5] G. Li, “Electromyography Pattern-Recognition-Based Control of Powered Multifunctional Upper-Limb Prostheses,” Advances in Applied Electromyography, Aug. 2011.
[6] Tijana Nosek, Branko Brkljač, Danica Despotović, Milan Sečujski, Tatjana Lončar-Turukalo, “Praktikum iz mašinskog učenja”, Univerzitet u Novom Sadu, 2020.
[7] Yang, Li, and Abdallah Shami. “On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice.” Neurocomputing, Vol. 415, pp. 295–316, Nov. 2020.
Objavljeno
2024-10-09
Sekcija
Biomedicinsko inženjerstvo
