| Title: |
Effects of deep brain stimulation of the subthalamic nucleus on patients with Parkinson's disease: a machine-learning voice analysis |
| Authors: |
Suppa A.; Asci F.; Costantini G.; Bove F.; Piano C.; Pistoia F.; Cerroni R.; Brusa L.; Cesarini V.; Pietracupa S.; Modugno N.; Zampogna A.; Sucapane P.; Pierantozzi M.; Tufo T.; Pisani A.; Peppe A.; Stefani A.; Calabresi P.; Bentivoglio A. R.; Saggio G. |
| Contributors: |
Suppa, A; Asci, F; Costantini, G; Bove, F; Piano, C; Pistoia, F; Cerroni, R; Brusa, L; Cesarini, V; Pietracupa, S; Modugno, N; Zampogna, A; Sucapane, P; Pierantozzi, M; Tufo, T; Pisani, A; Peppe, A; Stefani, A; Calabresi, P; Bentivoglio, Ar; Saggio, G |
| Publisher Information: |
Frontiers Media SA |
| Publication Year: |
2023 |
| Collection: |
Universitá degli Studi di Roma "Tor Vergata": ART - Archivio Istituzionale della Ricerca |
| Subject Terms: |
deep brain stimulation; machine-learning; Parkinson's disease; subthalamic nucleus; voice analysis; Settore MED/26 |
| Description: |
introduction: deep brain stimulation of the subthalamic nucleus (STN-DBS) can exert relevant effects on the voice of patients with parkinson's disease (PD). In this study, we used artificial intelligence to objectively analyze the voices of PD patients with STN-DBS. materials and methods: In a cross-sectional study, we enrolled 108 controls and 101 patients with PD. the cohort of PD was divided into two groups: the first group included 50 patients with STN-DBS, and the second group included 51 patients receiving the best medical treatment. the voices were clinically evaluated using the unified parkinson's disease rating scale part-III subitem for voice (UPDRS-III-v). we recorded and then analyzed voices using specific machine-learning algorithms. the likelihood ratio (LR) was also calculated as an objective measure for clinical-instrumental correlations. results: clinically, voice impairment was greater in STN-DBS patients than in those who received oral treatment. Using machine learning, we objectively and accurately distinguished between the voices of STN-DBS patients and those under oral treatments. we also found significant clinical-instrumental correlations since the greater the LRs, the higher the UPDRS-III-v scores. discussion: STN-DBS deteriorates speech in patients with PD, as objectively demonstrated by machine-learning voice analysis. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
info:eu-repo/semantics/altIdentifier/pmid/37928137; info:eu-repo/semantics/altIdentifier/wos/WOS:001096239100001; volume:14; firstpage:1267360; journal:FRONTIERS IN NEUROLOGY; https://hdl.handle.net/2108/352850 |
| DOI: |
10.3389/fneur.2023.1267360 |
| Availability: |
https://hdl.handle.net/2108/352850; https://doi.org/10.3389/fneur.2023.1267360 |
| Rights: |
info:eu-repo/semantics/openAccess ; license:Creative commons ; license uri:http://creativecommons.org/licenses/by/4.0/ |
| Accession Number: |
edsbas.6E26D11C |
| Database: |
BASE |