Smartphone Voice Calls Provide Early Biomarkers of Parkinsonism in Rapid Eye Movement Sleep Behavior Disorder
Background Speech dysfunction represents one of the initial motor manifestations to develop in Parkinson's disease (PD) and is measurable through smartphone. Objective The aim was to develop a fully automated and noise‐resistant smartphone‐based system that can unobtrusively screen for prodroma...
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| Veröffentlicht in: | Movement disorders 2024-10, Vol.39 (10), p.1752-1762 |
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| creator | Illner, Vojtěch Novotný, Michal Kouba, Tomáš Tykalová, Tereza Šimek, Michal Sovka, Pavel Švihlík, Jan Růžička, Evžen Šonka, Karel Dušek, Petr Rusz, Jan |
| description | Background
Speech dysfunction represents one of the initial motor manifestations to develop in Parkinson's disease (PD) and is measurable through smartphone.
Objective
The aim was to develop a fully automated and noise‐resistant smartphone‐based system that can unobtrusively screen for prodromal parkinsonian speech disorder in subjects with isolated rapid eye movement sleep behavior disorder (iRBD) in a real‐world scenario.
Methods
This cross‐sectional study assessed regular, everyday voice call data from individuals with iRBD compared to early PD patients and healthy controls via a developed smartphone application. The participants also performed an active, regular reading of a short passage on their smartphone. Smartphone data were continuously collected for up to 3 months after the standard in‐person assessments at the clinic.
Results
A total of 3525 calls that led to 5990 minutes of preprocessed speech were extracted from 72 participants, comprising 21 iRBD patients, 26 PD patients, and 25 controls. With a high area under the curve of 0.85 between iRBD patients and controls, the combination of passive and active smartphone data provided a comparable or even more sensitive evaluation than laboratory examination using a high‐quality microphone. The most sensitive features to induce prodromal neurodegeneration in iRBD included imprecise vowel articulation during phone calls (P = 0.03) and monopitch in reading (P = 0.05). Eighteen minutes of speech corresponding to approximately nine calls was sufficient to obtain the best sensitivity for the screening.
Conclusion
We consider the developed tool widely applicable to deep longitudinal digital phenotyping data with future applications in neuroprotective trials, deep brain stimulation optimization, neuropsychiatry, speech therapy, population screening, and beyond. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. |
| doi_str_mv | 10.1002/mds.29921 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_3079860328</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3079860328</sourcerecordid><originalsourceid>FETCH-LOGICAL-c2781-6f8ff8bf360c7ee6e7ec7d4641b9bae116005b9f34b84a26ff192017dfb8085b3</originalsourceid><addsrcrecordid>eNp10cFOGzEQBmALUZFAe-AFkCUu9LDgsbNe7xFCoJWCipqWq-XdHSsOu-vFTlLl7WsayqFSTzOHT79G8xNyCuwSGONXXRMveVlyOCBjyAVkiufFIRkzpfJMgMpH5DjGFWMAOcgjMhJl2qWQY9ItOhPWw9L3SJ-8q5FOTdtG-hj81jVIZya0O3rjfGLPGCL1lj6m1fXR9y521PX0uxlcQ2c7pA9-ix32a7poEQd6g0uzdT7QWxd9aDB8JB-saSN-epsn5Ofd7Mf0Szb_dv91ej3Pal4oyKRV1qrKCsnqAlFigXXRTOQEqrIyCCAZy6vSikmlJoZLa6HkDIrGVoqpvBIn5GKfOwT_ssG41p2LNbat6dFvohasKJVkgqtEz_-hK78JfbpOCwAFBeMCkvq8V3XwMQa0egguvWSngenXDnTqQP_pINmzt8RN1WHzLv8-PYGrPfjlWtz9P0k_3C72kb8BzaaQRg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3118170231</pqid></control><display><type>article</type><title>Smartphone Voice Calls Provide Early Biomarkers of Parkinsonism in Rapid Eye Movement Sleep Behavior Disorder</title><source>Wiley Online Library Journals Frontfile Complete</source><creator>Illner, Vojtěch ; Novotný, Michal ; Kouba, Tomáš ; Tykalová, Tereza ; Šimek, Michal ; Sovka, Pavel ; Švihlík, Jan ; Růžička, Evžen ; Šonka, Karel ; Dušek, Petr ; Rusz, Jan</creator><creatorcontrib>Illner, Vojtěch ; Novotný, Michal ; Kouba, Tomáš ; Tykalová, Tereza ; Šimek, Michal ; Sovka, Pavel ; Švihlík, Jan ; Růžička, Evžen ; Šonka, Karel ; Dušek, Petr ; Rusz, Jan</creatorcontrib><description>Background
Speech dysfunction represents one of the initial motor manifestations to develop in Parkinson's disease (PD) and is measurable through smartphone.
Objective
The aim was to develop a fully automated and noise‐resistant smartphone‐based system that can unobtrusively screen for prodromal parkinsonian speech disorder in subjects with isolated rapid eye movement sleep behavior disorder (iRBD) in a real‐world scenario.
Methods
This cross‐sectional study assessed regular, everyday voice call data from individuals with iRBD compared to early PD patients and healthy controls via a developed smartphone application. The participants also performed an active, regular reading of a short passage on their smartphone. Smartphone data were continuously collected for up to 3 months after the standard in‐person assessments at the clinic.
Results
A total of 3525 calls that led to 5990 minutes of preprocessed speech were extracted from 72 participants, comprising 21 iRBD patients, 26 PD patients, and 25 controls. With a high area under the curve of 0.85 between iRBD patients and controls, the combination of passive and active smartphone data provided a comparable or even more sensitive evaluation than laboratory examination using a high‐quality microphone. The most sensitive features to induce prodromal neurodegeneration in iRBD included imprecise vowel articulation during phone calls (P = 0.03) and monopitch in reading (P = 0.05). Eighteen minutes of speech corresponding to approximately nine calls was sufficient to obtain the best sensitivity for the screening.
Conclusion
We consider the developed tool widely applicable to deep longitudinal digital phenotyping data with future applications in neuroprotective trials, deep brain stimulation optimization, neuropsychiatry, speech therapy, population screening, and beyond. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.</description><identifier>ISSN: 0885-3185</identifier><identifier>ISSN: 1531-8257</identifier><identifier>EISSN: 1531-8257</identifier><identifier>DOI: 10.1002/mds.29921</identifier><identifier>PMID: 39001636</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>Basal ganglia ; Behavior disorders ; Calling behavior ; Central nervous system diseases ; Clinical trials ; Deep brain stimulation ; Eye movements ; machine learning ; Movement disorders ; Neurodegeneration ; Neurodegenerative diseases ; Neuroprotection ; Parkinson's disease ; Phenotyping ; prodromal synucleinopathy biomarker ; REM sleep ; Sensitivity analysis ; Sleep disorders ; Smartphones ; Speech ; wearables</subject><ispartof>Movement disorders, 2024-10, Vol.39 (10), p.1752-1762</ispartof><rights>2024 The Author(s). published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.</rights><rights>2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.</rights><rights>2024. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2781-6f8ff8bf360c7ee6e7ec7d4641b9bae116005b9f34b84a26ff192017dfb8085b3</cites><orcidid>0000-0002-4893-9661 ; 0000-0003-4877-9642 ; 0000-0002-1036-3054</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fmds.29921$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fmds.29921$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39001636$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Illner, Vojtěch</creatorcontrib><creatorcontrib>Novotný, Michal</creatorcontrib><creatorcontrib>Kouba, Tomáš</creatorcontrib><creatorcontrib>Tykalová, Tereza</creatorcontrib><creatorcontrib>Šimek, Michal</creatorcontrib><creatorcontrib>Sovka, Pavel</creatorcontrib><creatorcontrib>Švihlík, Jan</creatorcontrib><creatorcontrib>Růžička, Evžen</creatorcontrib><creatorcontrib>Šonka, Karel</creatorcontrib><creatorcontrib>Dušek, Petr</creatorcontrib><creatorcontrib>Rusz, Jan</creatorcontrib><title>Smartphone Voice Calls Provide Early Biomarkers of Parkinsonism in Rapid Eye Movement Sleep Behavior Disorder</title><title>Movement disorders</title><addtitle>Mov Disord</addtitle><description>Background
Speech dysfunction represents one of the initial motor manifestations to develop in Parkinson's disease (PD) and is measurable through smartphone.
Objective
The aim was to develop a fully automated and noise‐resistant smartphone‐based system that can unobtrusively screen for prodromal parkinsonian speech disorder in subjects with isolated rapid eye movement sleep behavior disorder (iRBD) in a real‐world scenario.
Methods
This cross‐sectional study assessed regular, everyday voice call data from individuals with iRBD compared to early PD patients and healthy controls via a developed smartphone application. The participants also performed an active, regular reading of a short passage on their smartphone. Smartphone data were continuously collected for up to 3 months after the standard in‐person assessments at the clinic.
Results
A total of 3525 calls that led to 5990 minutes of preprocessed speech were extracted from 72 participants, comprising 21 iRBD patients, 26 PD patients, and 25 controls. With a high area under the curve of 0.85 between iRBD patients and controls, the combination of passive and active smartphone data provided a comparable or even more sensitive evaluation than laboratory examination using a high‐quality microphone. The most sensitive features to induce prodromal neurodegeneration in iRBD included imprecise vowel articulation during phone calls (P = 0.03) and monopitch in reading (P = 0.05). Eighteen minutes of speech corresponding to approximately nine calls was sufficient to obtain the best sensitivity for the screening.
Conclusion
We consider the developed tool widely applicable to deep longitudinal digital phenotyping data with future applications in neuroprotective trials, deep brain stimulation optimization, neuropsychiatry, speech therapy, population screening, and beyond. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.</description><subject>Basal ganglia</subject><subject>Behavior disorders</subject><subject>Calling behavior</subject><subject>Central nervous system diseases</subject><subject>Clinical trials</subject><subject>Deep brain stimulation</subject><subject>Eye movements</subject><subject>machine learning</subject><subject>Movement disorders</subject><subject>Neurodegeneration</subject><subject>Neurodegenerative diseases</subject><subject>Neuroprotection</subject><subject>Parkinson's disease</subject><subject>Phenotyping</subject><subject>prodromal synucleinopathy biomarker</subject><subject>REM sleep</subject><subject>Sensitivity analysis</subject><subject>Sleep disorders</subject><subject>Smartphones</subject><subject>Speech</subject><subject>wearables</subject><issn>0885-3185</issn><issn>1531-8257</issn><issn>1531-8257</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><recordid>eNp10cFOGzEQBmALUZFAe-AFkCUu9LDgsbNe7xFCoJWCipqWq-XdHSsOu-vFTlLl7WsayqFSTzOHT79G8xNyCuwSGONXXRMveVlyOCBjyAVkiufFIRkzpfJMgMpH5DjGFWMAOcgjMhJl2qWQY9ItOhPWw9L3SJ-8q5FOTdtG-hj81jVIZya0O3rjfGLPGCL1lj6m1fXR9y521PX0uxlcQ2c7pA9-ix32a7poEQd6g0uzdT7QWxd9aDB8JB-saSN-epsn5Ofd7Mf0Szb_dv91ej3Pal4oyKRV1qrKCsnqAlFigXXRTOQEqrIyCCAZy6vSikmlJoZLa6HkDIrGVoqpvBIn5GKfOwT_ssG41p2LNbat6dFvohasKJVkgqtEz_-hK78JfbpOCwAFBeMCkvq8V3XwMQa0egguvWSngenXDnTqQP_pINmzt8RN1WHzLv8-PYGrPfjlWtz9P0k_3C72kb8BzaaQRg</recordid><startdate>202410</startdate><enddate>202410</enddate><creator>Illner, Vojtěch</creator><creator>Novotný, Michal</creator><creator>Kouba, Tomáš</creator><creator>Tykalová, Tereza</creator><creator>Šimek, Michal</creator><creator>Sovka, Pavel</creator><creator>Švihlík, Jan</creator><creator>Růžička, Evžen</creator><creator>Šonka, Karel</creator><creator>Dušek, Petr</creator><creator>Rusz, Jan</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TK</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-4893-9661</orcidid><orcidid>https://orcid.org/0000-0003-4877-9642</orcidid><orcidid>https://orcid.org/0000-0002-1036-3054</orcidid></search><sort><creationdate>202410</creationdate><title>Smartphone Voice Calls Provide Early Biomarkers of Parkinsonism in Rapid Eye Movement Sleep Behavior Disorder</title><author>Illner, Vojtěch ; Novotný, Michal ; Kouba, Tomáš ; Tykalová, Tereza ; Šimek, Michal ; Sovka, Pavel ; Švihlík, Jan ; Růžička, Evžen ; Šonka, Karel ; Dušek, Petr ; Rusz, Jan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2781-6f8ff8bf360c7ee6e7ec7d4641b9bae116005b9f34b84a26ff192017dfb8085b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Basal ganglia</topic><topic>Behavior disorders</topic><topic>Calling behavior</topic><topic>Central nervous system diseases</topic><topic>Clinical trials</topic><topic>Deep brain stimulation</topic><topic>Eye movements</topic><topic>machine learning</topic><topic>Movement disorders</topic><topic>Neurodegeneration</topic><topic>Neurodegenerative diseases</topic><topic>Neuroprotection</topic><topic>Parkinson's disease</topic><topic>Phenotyping</topic><topic>prodromal synucleinopathy biomarker</topic><topic>REM sleep</topic><topic>Sensitivity analysis</topic><topic>Sleep disorders</topic><topic>Smartphones</topic><topic>Speech</topic><topic>wearables</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Illner, Vojtěch</creatorcontrib><creatorcontrib>Novotný, Michal</creatorcontrib><creatorcontrib>Kouba, Tomáš</creatorcontrib><creatorcontrib>Tykalová, Tereza</creatorcontrib><creatorcontrib>Šimek, Michal</creatorcontrib><creatorcontrib>Sovka, Pavel</creatorcontrib><creatorcontrib>Švihlík, Jan</creatorcontrib><creatorcontrib>Růžička, Evžen</creatorcontrib><creatorcontrib>Šonka, Karel</creatorcontrib><creatorcontrib>Dušek, Petr</creatorcontrib><creatorcontrib>Rusz, Jan</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Movement disorders</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Illner, Vojtěch</au><au>Novotný, Michal</au><au>Kouba, Tomáš</au><au>Tykalová, Tereza</au><au>Šimek, Michal</au><au>Sovka, Pavel</au><au>Švihlík, Jan</au><au>Růžička, Evžen</au><au>Šonka, Karel</au><au>Dušek, Petr</au><au>Rusz, Jan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Smartphone Voice Calls Provide Early Biomarkers of Parkinsonism in Rapid Eye Movement Sleep Behavior Disorder</atitle><jtitle>Movement disorders</jtitle><addtitle>Mov Disord</addtitle><date>2024-10</date><risdate>2024</risdate><volume>39</volume><issue>10</issue><spage>1752</spage><epage>1762</epage><pages>1752-1762</pages><issn>0885-3185</issn><issn>1531-8257</issn><eissn>1531-8257</eissn><abstract>Background
Speech dysfunction represents one of the initial motor manifestations to develop in Parkinson's disease (PD) and is measurable through smartphone.
Objective
The aim was to develop a fully automated and noise‐resistant smartphone‐based system that can unobtrusively screen for prodromal parkinsonian speech disorder in subjects with isolated rapid eye movement sleep behavior disorder (iRBD) in a real‐world scenario.
Methods
This cross‐sectional study assessed regular, everyday voice call data from individuals with iRBD compared to early PD patients and healthy controls via a developed smartphone application. The participants also performed an active, regular reading of a short passage on their smartphone. Smartphone data were continuously collected for up to 3 months after the standard in‐person assessments at the clinic.
Results
A total of 3525 calls that led to 5990 minutes of preprocessed speech were extracted from 72 participants, comprising 21 iRBD patients, 26 PD patients, and 25 controls. With a high area under the curve of 0.85 between iRBD patients and controls, the combination of passive and active smartphone data provided a comparable or even more sensitive evaluation than laboratory examination using a high‐quality microphone. The most sensitive features to induce prodromal neurodegeneration in iRBD included imprecise vowel articulation during phone calls (P = 0.03) and monopitch in reading (P = 0.05). Eighteen minutes of speech corresponding to approximately nine calls was sufficient to obtain the best sensitivity for the screening.
Conclusion
We consider the developed tool widely applicable to deep longitudinal digital phenotyping data with future applications in neuroprotective trials, deep brain stimulation optimization, neuropsychiatry, speech therapy, population screening, and beyond. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><pmid>39001636</pmid><doi>10.1002/mds.29921</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-4893-9661</orcidid><orcidid>https://orcid.org/0000-0003-4877-9642</orcidid><orcidid>https://orcid.org/0000-0002-1036-3054</orcidid><oa>free_for_read</oa></addata></record> |
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| source | Wiley Online Library Journals Frontfile Complete |
| subjects | Basal ganglia Behavior disorders Calling behavior Central nervous system diseases Clinical trials Deep brain stimulation Eye movements machine learning Movement disorders Neurodegeneration Neurodegenerative diseases Neuroprotection Parkinson's disease Phenotyping prodromal synucleinopathy biomarker REM sleep Sensitivity analysis Sleep disorders Smartphones Speech wearables |
| title | Smartphone Voice Calls Provide Early Biomarkers of Parkinsonism in Rapid Eye Movement Sleep Behavior Disorder |
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