{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T15:50:03Z","timestamp":1791474603631,"version":"4.3.4"},"reference-count":41,"publisher":"Walter de Gruyter GmbH","issue":"4-5","license":[{"start":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T00:00:00Z","timestamp":1785110400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Outstanding Youth Project of Hunan Provincial Department of Education","award":["23B0868"],"award-info":[{"award-number":["23B0868"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,10,26]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec id=\"j_bmt-2026-0357_abs_001\">\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Parkinson\u2019s disease (PD) can affect vocal production before severe motor symptoms become apparent. This study presents a device-oriented dual-route voice-screening framework that combines interpretable acoustic descriptors with spectrogram-based transfer learning for PD assessment support.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_bmt-2026-0357_abs_002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Publicly available sustained-vowel \/a\/ recordings from the Parkinson Speech Dataset with Multiple Types of Sound Recordings were used for algorithmic evaluation. The proposed handheld device, dashboard, and connectivity workflow were treated as a conceptual deployment scenario. The acoustic route generated an integrated acoustic-feature vector and grouped representation-level summaries of selected descriptor families. The spectrogram route generated RGB color-mapped and grayscale time-frequency representations, which were processed using an EfficientNet-B0 transfer-learning convolutional neural network.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_bmt-2026-0357_abs_003\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Among conventional acoustic-feature classifiers, the Ensemble Boosting Classifier achieved the highest AUC point estimate for the integrated acoustic-feature route. Grouped representation-level evidence showed weak-to-moderate discrimination for acoustic descriptor families. RGB and grayscale spectrograms processed through the EfficientNet-B0 route produced reported AUC point estimates of 0.93 and 0.89, respectively, within the available public-dataset evaluation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_bmt-2026-0357_abs_004\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The proposed framework combines interpretable acoustic descriptors and spectrogram-based transfer learning within a device-oriented screening-support workflow. Integrated acoustic features support interpretable reporting, while spectrogram-based transfer learning provides higher representation-level discrimination. Future validation with physical prototypes, standardized acquisition protocols, and independent clinical cohorts is required before clinical deployment.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1515\/bmt-2026-0357","type":"journal-article","created":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T15:56:11Z","timestamp":1784908571000},"page":"629-642","source":"Crossref","is-referenced-by-count":1,"title":["Design of a dual-route acoustic-feature and EfficientNet-B0 spectrogram-based voice-screening device for Parkinson\u2019s disease assessment"],"prefix":"10.1515","volume":"71","author":[{"given":"Wenxiang","family":"Zhou","sequence":"first","affiliation":[{"name":"Department of Product Design , Hunan International Economics University , Changsha , China"},{"name":"Faculty of Applied Sciences , Macao Polytechnic University , Macao , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziwei","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Product Design , Hunan International Economics University , Changsha , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shujuan","family":"Luo","sequence":"additional","affiliation":[{"name":"Department of Product Design , Hunan International Economics University , Changsha , China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"374","published-online":{"date-parts":[[2026,7,27]]},"reference":[{"key":"2026100814512972814_j_bmt-2026-0357_ref_001","doi-asserted-by":"crossref","unstructured":"Postuma, RB, Berg, D, Stern, M, Poewe, W, Olanow, CW, Oertel, W, et al.. 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