{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T18:35:46Z","timestamp":1792521346073,"version":"4.5.0"},"reference-count":51,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T00:00:00Z","timestamp":1781481600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Bioinform."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>\n                      Precise identification of motor states in Parkinson\u2019s disease (PD) is critical for adaptive deep brain stimulation (aDBS) therapies. Recent developments in implantable neurostimulators now support continuous neural recordings, enabling long-term monitoring of PD-related neural dynamics under real-world conditions. However, the real potential of such deep brain continuous recordings in chronic home-based conditions has not been explored yet. In this work, we introduce a multimodal classification framework that integrates subthalamic nucleus local field potentials (STN-LFPs), wearable sensors, and patient-reported diaries to distinguish between three key motor states:\n                      <jats:italic>ON<\/jats:italic>\n                      ,\n                      <jats:italic>OFF<\/jats:italic>\n                      , and\n                      <jats:italic>SLEEP<\/jats:italic>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The framework was initially validated on data collected from three patients over an average of 30 days (totaling 2,136 h of LFP recordings), and then applied to a larger dataset from thirteen patients recorded over an average of 14 days (totaling 4,440 h of LFP recordings). Feature extraction was performed in the time, frequency and time-frequency domains, after applying principal component analysis (PCA) to decrease dimensionality, which preserved 95% of the variance of the data and reduced computational complexity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The multilayer perceptron (MLP) classifier using time\u2013frequency domain features achieved the highest F1-score among the models tested. For the three validation patients, the MLP reached F1-scores of 81.1% with wearable sensor data and 94.3% with diary-derived data. When evaluated across all thirteen patients, it maintained a strong F1-score of 93.1% using diary time\u2013frequency features.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>These results demonstrate that chronic LFP recordings available 24\/7 from implantable aDBS devices enable robust motor state classification, thus supporting the personalization and optimization of aDBS systems for real-life use.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fbinf.2026.1820165","type":"journal-article","created":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T05:37:15Z","timestamp":1781501835000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Real-world chronic recordings from implantable adaptive deep brain stimulation systems for Parkinson\u2019s disease motor state classification"],"prefix":"10.3389","volume":"6","author":[{"given":"Hanan Awad Hassan","family":"Ali","sequence":"first","affiliation":[{"name":"Dipartimento di Matematica, Informatica e Geoscienze, Universit\u00e0 degli Studi di Trieste","place":["Trieste, Italy"]},{"name":"Faculty of Computers and Informatics, Suez Canal University","place":["Ismailia, Egypt"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matteo","family":"Guidetti","sequence":"additional","affiliation":[{"name":"Dipartimento di Scienze della Salute, Aldo Ravelli Research Center for Neurotechnology and Experimental Neurotherapeutics, Universit\u00e0 degli Studi di Milano","place":["Milan, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura","family":"Caffi","sequence":"additional","affiliation":[{"name":"University Hospital of W\u00fcrzburg and Julius Maximilian University of W\u00fcrzburg","place":["W\u00fcrzburg, Germany"]},{"name":"The BioRobotics Institute, Sant\u2019Anna School of Advanced Studies","place":["Pisa, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mattia","family":"Arlotti","sequence":"additional","affiliation":[{"name":"Newronika SpA","place":["Milan, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lorenzo","family":"Rossi","sequence":"additional","affiliation":[{"name":"Newronika SpA","place":["Milan, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chiara","family":"Palmisano","sequence":"additional","affiliation":[{"name":"University Hospital of W\u00fcrzburg and Julius Maximilian University of W\u00fcrzburg","place":["W\u00fcrzburg, Germany"]},{"name":"Fondazione Pezzoli per la Malattia di Parkinson","place":["Milan, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alberto","family":"Priori","sequence":"additional","affiliation":[{"name":"Dipartimento di Scienze della Salute, Aldo Ravelli Research Center for Neurotechnology and Experimental Neurotherapeutics, Universit\u00e0 degli Studi di Milano","place":["Milan, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Brun","sequence":"additional","affiliation":[{"name":"Department of Engineering and Architecture, University of Trieste","place":["Trieste, Italy"]},{"name":"Trieste Division, National Institute for Nuclear Physics (INFN)","place":["Trieste, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ioannis Ugo","family":"Isaias","sequence":"additional","affiliation":[{"name":"University Hospital of W\u00fcrzburg and Julius Maximilian University of W\u00fcrzburg","place":["W\u00fcrzburg, Germany"]},{"name":"Parkinson Institute of Milan, ASST G. 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