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Rusz J, Krack P, Tripoliti E. From prodromal stages to clinical trials: The promise of digital speech biomarkers in Parkinson's disease. Neurosci Biobehav Rev 2024; 167:105922. [PMID: 39424108 DOI: 10.1016/j.neubiorev.2024.105922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2024] [Revised: 09/19/2024] [Accepted: 10/13/2024] [Indexed: 10/21/2024]
Abstract
Speech impairment is a common and disabling symptom in Parkinson's disease (PD), affecting communication and quality of life. Advances in digital speech processing and artificial intelligence have revolutionized objective speech analysis. Given the complex nature of speech impairment, acoustic speech analysis offers unique biomarkers for neuroprotective treatments from the prodromal stages of PD. Digital speech biomarkers can monitor levodopa-induced motor complications, detect the effects of deep brain stimulation, and provide feedback for behavioral speech therapy. This review updates the mechanisms underlying speech impairment, the impact of speech phenotypes, and the effects of interventions on speech. We evaluate the strengths, potential weaknesses, and suitability of promising digital speech biomarkers in PD for capturing disease progression and treatment efficacy. Additionally, we explore the translational potential of PD speech biomarkers to other neuropsychiatric diseases, offering insights into motion, cognition, and emotion. Finally, we highlight knowledge gaps and suggest directions for future research to enhance the use of quantitative speech measures in disease-modifying clinical trials. The findings demonstrate that one year is sufficient to detect disease progression in early PD through speech biomarkers. Voice quality, pitch, loudness, and articulation measures appear to capture the efficacy of treatment interventions most effectively. Certain speech features, such as loudness and articulation rate, behave oppositely in different neurological diseases, offering valuable insights for differential diagnosis. In conclusion, this review highlights speech as a biomarker in tracking disease progression, especially in the prodromal stages of PD, and calls for further longitudinal studies to establish its efficacy across diverse populations.
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Affiliation(s)
- Jan Rusz
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
| | - Paul Krack
- Movement Disorders Center, Department of Neurology, University Hospital of Bern, Bern, Switzerland
| | - Elina Tripoliti
- UCL, Institute of Neurology, Department of Clinical and Movement Neurosciences, and National Hospital for Neurology and Neurosurgery, UCLH NHS Trust, London, UK
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Illner V, Novotný M, Kouba T, Tykalová T, Šimek M, Sovka P, Švihlík J, Růžička E, Šonka K, Dušek P, Rusz J. Smartphone Voice Calls Provide Early Biomarkers of Parkinsonism in Rapid Eye Movement Sleep Behavior Disorder. Mov Disord 2024; 39:1752-1762. [PMID: 39001636 DOI: 10.1002/mds.29921] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 06/03/2024] [Accepted: 06/21/2024] [Indexed: 09/05/2024] Open
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.
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Affiliation(s)
- Vojtěch Illner
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Michal Novotný
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Tomáš Kouba
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Tereza Tykalová
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Michal Šimek
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Pavel Sovka
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Jan Švihlík
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
- Department of Mathematics, Informatics and Cybernetics, Faculty of Chemical Engineering, University of Chemistry and Technology, Prague, Czech Republic
| | - Evžen Růžička
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Karel Šonka
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Petr Dušek
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Jan Rusz
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
- Department of Neurology and ARTORG Center, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
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Convey RB, Laukkanen AM, Ylinen S, Penttilä N. Analysis of Voice Changes in Early-Stage Parkinson's Disease with AVQI and ABI: A Follow-up Study. J Voice 2024:S0892-1997(24)00160-7. [PMID: 38897855 DOI: 10.1016/j.jvoice.2024.05.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 05/17/2024] [Accepted: 05/18/2024] [Indexed: 06/21/2024]
Abstract
OBJECTIVES The purpose of this pilot study was to examine voice quality changes in individuals with early-stage Parkinson's disease (PD) utilizing the Acoustic Voice Quality Index (AVQI) and Acoustic Breathiness Index (ABI) over approximately a 1-year period. STUDY DESIGN Follow-up study. METHODS Baseline and follow-up data were gathered from the PDSTUlong speech corpus. The data for both time points included: speaker background information, sustained vowels, reading samples, and measures of PD severity (Hoehn and Yahr scores and Unified Parkinson's Disease Rating Scale III scores [UPDRS-III]). All speakers (N = 12) were native Finnish speakers. AVQIv03.01 and ABI analysis were completed in VOXplot v2.0.1. Changes in AVQI and ABI scores between baseline and follow-up were examined via causal analysis. Further, AVQI and ABI were analyzed in relation to measures of PD severity. RESULTS Baseline mean AVQI score was 1.79 (range 0.14-4.83, SD=1.60), whereas follow-up mean AVQI score was 2.25 (range 0.55-4.53, SD=1.36). Baseline mean ABI score, in turn, was 2.92 (range 1-27 - 5.31, SD=1.57), whereas follow-up mean ABI score was 3.42 (range 1.40-5.40, SD=1.38). A significant difference was found between baseline and follow-up measures for both AVQI (Z = -2.002, P = 0.045) and ABI (Z = -2.197, P = 0.028). A significant difference in smoothed cepstral peak prominence (Z = -2.118, P = 0.034) and harmonics-to-noise ratio (Z = -1.961, P = 0.050) was also found between the two measurement periods. Change in AVQI and ABI were not correlated with the change in measures of PD severity. CONCLUSION Over approximately 1-year, a statistical change was observed in AVQI and ABI scores, even in such a small dataset. The specific qualities of breathiness and hoarseness showed the most significant progression. Changes in voice quality were more prominent in ABI analysis.
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Affiliation(s)
- Rachel B Convey
- Faculty of Social Sciences, Tampere University, Tampere, Finland.
| | | | - Sari Ylinen
- Faculty of Social Sciences, Tampere University, Tampere, Finland
| | - Nelly Penttilä
- Faculty of Social Sciences, Tampere University, Tampere, Finland
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Houle N, Feaster T, Mira A, Meeks K, Stepp CE. Sex Differences in the Speech of Persons With and Without Parkinson's Disease. AMERICAN JOURNAL OF SPEECH-LANGUAGE PATHOLOGY 2024; 33:96-116. [PMID: 37889201 PMCID: PMC11000784 DOI: 10.1044/2023_ajslp-22-00350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 02/24/2023] [Accepted: 08/30/2023] [Indexed: 10/28/2023]
Abstract
BACKGROUND Sex differences are apparent in the prevalence and the clinical presentation of Parkinson's disease (PD), but their effects on speech have been less studied. METHOD Speech acoustics of persons with (34 females and 34 males) and without (age- and sex-matched) PD were examined, assessing the effects of PD diagnosis and sex on ratings of dysarthria severity and acoustic measures of phonation (fundamental frequency standard deviation, smoothed cepstral peak prominence), speech rate (net syllables per second, percent pause ratio), and articulation (articulatory-acoustic vowel space, release burst precision). RESULTS Most measures were affected by PD (dysarthria severity, fundamental frequency standard deviation) and sex (smoothed cepstral peak prominence, net syllables per second, percent pause ratio, articulatory-acoustic vowel space), but without interactions between them. Release burst precision was differentially affected by sex in PD. Relative to those without PD, persons with PD produced fewer plosives with a single burst: females more frequently produced multiple bursts, whereas males more frequently produced no burst at all. CONCLUSIONS Most metrics did not indicate that speech production is differentially affected by sex in PD. Sex was, however, associated with disparate effects on release burst precision in PD, which deserves further study. SUPPLEMENTAL MATERIAL https://doi.org/10.23641/asha.24388666.
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Affiliation(s)
- Nichole Houle
- Department of Speech, Language, and Hearing Sciences, Boston University, MA
| | - Taylor Feaster
- Department of Speech, Language, and Hearing Sciences, Boston University, MA
| | - Amna Mira
- Department of Speech, Language, and Hearing Sciences, Boston University, MA
- College of Applied Medical Sciences, King Saud bin Abdulaziz University for Health Sciences, Jeddah, Saudi Arabia
- King Abdullah International Medical Research Center, Jeddah, Saudi Arabia
| | - Kirsten Meeks
- Department of Speech, Language, and Hearing Sciences, Boston University, MA
| | - Cara E. Stepp
- Department of Speech, Language, and Hearing Sciences, Boston University, MA
- Department of Biomedical Engineering, Boston University, MA
- Department of Otolaryngology–Head & Neck Surgery, Boston University School of Medicine, MA
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Boogers A, Peeters J, Van Bogaert T, Rusz J, Bogaert-Miclaus C, Loret G, De Vloo P, Vandenberghe W, Nuttin B, Mc Laughlin M. Acute stimulation with symmetric biphasic pulses induces less ataxia compared to cathodic pulses in DBS for essential tremor. Parkinsonism Relat Disord 2023; 111:105435. [PMID: 37187082 DOI: 10.1016/j.parkreldis.2023.105435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/23/2023] [Accepted: 04/29/2023] [Indexed: 05/17/2023]
Abstract
BACKGROUND Symmetric biphasic pulses have been shown to acutely increase the therapeutic window of ventralis intermedius deep brain stimulation (Vim-DBS) for essential tremor (ET) compared to cathodic pulses. Acute supratherapeutic stimulation can induce ataxic side effects in Vim-DBS. OBJECTIVE To investigate the effect on tremor, ataxia and dysarthria of 3 h of biphasic stimulation in patients with DBS for ET. METHODS A randomized, doubled-blind, cross-over design was used to compare standard cathodic pulses with symmetric biphasic pulses (anode-first) during a 3-h period per pulse shape. During each 3-h period, all stimulation parameters were identical, except for the pulse shape. Tremor (Fahn-Tolosa-Marin Tremor Rating Scale), ataxia (International Cooperative Ataxia Rating Scale) and speech (acoustic and perceptual measures) were assessed hourly during the 3-h periods. RESULTS Twelve ET patients were included. During the 3-h stimulation period, tremor control was equivalent between the two pulse shapes. Biphasic pulses elicited significantly less ataxia than cathodic pulses (p = 0.006). Diadochokinesis rate of speech was better for the biphasic pulse (p = 0.048), but other measures for dysarthria were not significantly different between the pulses. CONCLUSION Symmetric biphasic pulses induce less ataxia than conventional pulses after 3 h of stimulation DBS in ET patients.
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Affiliation(s)
- Alexandra Boogers
- Exp ORL, Department of Neurosciences, The Leuven Brain Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium; Department of Neurology, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Jana Peeters
- Exp ORL, Department of Neurosciences, The Leuven Brain Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Tine Van Bogaert
- Exp ORL, Department of Neurosciences, The Leuven Brain Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Jan Rusz
- Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Technicka 2, 160 00, Prague 6, Czech Republic
| | | | - Griet Loret
- Department of Neurology, AZ Sint-Lucas, Groenebriel 1, 9000, Gent, Belgium
| | - Philippe De Vloo
- Department of Neurosurgery, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium; Experimental Neurosurgery and Neuroanatomy, Department of Neurosciences, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Wim Vandenberghe
- Department of Neurology, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium; Laboratory for Parkinson Research, Department of Neurosciences, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Bart Nuttin
- Department of Neurosurgery, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium; Experimental Neurosurgery and Neuroanatomy, Department of Neurosciences, KU Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Myles Mc Laughlin
- Exp ORL, Department of Neurosciences, The Leuven Brain Institute, KU Leuven, Herestraat 49, 3000, Leuven, Belgium.
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Adams JL, Kangarloo T, Tracey B, O'Donnell P, Volfson D, Latzman RD, Zach N, Alexander R, Bergethon P, Cosman J, Anderson D, Best A, Severson J, Kostrzebski MA, Auinger P, Wilmot P, Pohlson Y, Waddell E, Jensen-Roberts S, Gong Y, Kilambi KP, Herrero TR, Ray Dorsey E. Using a smartwatch and smartphone to assess early Parkinson's disease in the WATCH-PD study. NPJ Parkinsons Dis 2023; 9:64. [PMID: 37069193 PMCID: PMC10108794 DOI: 10.1038/s41531-023-00497-x] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 02/27/2023] [Indexed: 04/19/2023] Open
Abstract
Digital health technologies can provide continuous monitoring and objective, real-world measures of Parkinson's disease (PD), but have primarily been evaluated in small, single-site studies. In this 12-month, multicenter observational study, we evaluated whether a smartwatch and smartphone application could measure features of early PD. 82 individuals with early, untreated PD and 50 age-matched controls wore research-grade sensors, a smartwatch, and a smartphone while performing standardized assessments in the clinic. At home, participants wore the smartwatch for seven days after each clinic visit and completed motor, speech and cognitive tasks on the smartphone every other week. Features derived from the devices, particularly arm swing, the proportion of time with tremor, and finger tapping, differed significantly between individuals with early PD and age-matched controls and had variable correlation with traditional assessments. Longitudinal assessments will inform the value of these digital measures for use in future clinical trials.
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Affiliation(s)
- Jamie L Adams
- Center for Health + Technology, University of Rochester Medical Center, Rochester, NY, USA.
- Department of Neurology, University of Rochester Medical Center, Rochester, NY, USA.
| | | | | | - Patricio O'Donnell
- Takeda Pharmaceuticals, Cambridge, MA, USA
- Sage Therapeutics, Seattle, WA, USA
| | | | | | - Neta Zach
- Takeda Pharmaceuticals, Cambridge, MA, USA
| | - Robert Alexander
- Takeda Pharmaceuticals, Cambridge, MA, USA
- Banner Health, Phoenix, AZ, USA
| | | | | | | | | | | | - Melissa A Kostrzebski
- Center for Health + Technology, University of Rochester Medical Center, Rochester, NY, USA
- Department of Neurology, University of Rochester Medical Center, Rochester, NY, USA
| | - Peggy Auinger
- Center for Health + Technology, University of Rochester Medical Center, Rochester, NY, USA
- Department of Neurology, University of Rochester Medical Center, Rochester, NY, USA
| | - Peter Wilmot
- Center for Health + Technology, University of Rochester Medical Center, Rochester, NY, USA
| | - Yvonne Pohlson
- Center for Health + Technology, University of Rochester Medical Center, Rochester, NY, USA
| | - Emma Waddell
- Center for Health + Technology, University of Rochester Medical Center, Rochester, NY, USA
| | - Stella Jensen-Roberts
- Center for Health + Technology, University of Rochester Medical Center, Rochester, NY, USA
| | - Yishu Gong
- Takeda Pharmaceuticals, Cambridge, MA, USA
| | - Krishna Praneeth Kilambi
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Massachusetts Institute of Technology, Boston, MA, USA
| | | | - E Ray Dorsey
- Center for Health + Technology, University of Rochester Medical Center, Rochester, NY, USA
- Department of Neurology, University of Rochester Medical Center, Rochester, NY, USA
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Cordella C, Gutz SE, Eshghi M, Stipancic KL, Schliep M, Dickerson BC, Green JR. Acoustic and Kinematic Assessment of Motor Speech Impairment in Patients With Suspected Four-Repeat Tauopathies. JOURNAL OF SPEECH, LANGUAGE, AND HEARING RESEARCH : JSLHR 2022; 65:4112-4132. [PMID: 36306508 PMCID: PMC9940887 DOI: 10.1044/2022_jslhr-22-00177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
PURPOSE The aim of this study was to use acoustic and kinematic speech measures to characterize type of motor speech impairment-apraxia of speech (AOS) versus dysarthria-in individuals with four-repeat tauopathy (4RT)-associated syndromes, including nonfluent variant primary progressive aphasia (nfvPPA), primary progressive AOS (PPAOS), corticobasal syndrome (CBS), and progressive supranuclear palsy syndrome (PSPs). METHOD Twenty patient participants were recruited and stratified into two groups: (a) a motor-speech-impaired group of individuals with nfvPPA, PPAOS, CBS, or PSPs and suspected 4RT pathology ("MSI+") and (b) a non-motor-speech-impaired group of individuals with logopenic variant primary progressive aphasia ("MSI-"). Ten healthy, age-matched controls also participated in the study. Participants completed a battery of speech tasks, and 15 acoustic and kinematic speech measures were derived. Quantitative speech measures were grouped into feature categories ("AOS features," "dysarthria features," "shared features"). In addition to quantitative speech measures, two certified speech-language pathologists made independent, blinded auditory-perceptual ratings of motor speech impairment. A principal component analysis (PCA) was conducted to investigate the relative contributions of quantitative features. RESULTS Quantitative speech measures were generally concordant with independent clinician ratings of motor speech impairment severity. Hypothesis-driven groupings of quantitative measures differentiated predominantly apraxic from predominantly dysarthric presentations within the MSI+ group. PCA results provided additional evidence for differential profiles of motor speech impairment in the MSI+ group; heterogeneity across individuals is explained in large part by varying levels of overall severity-captured by the shared feature variable group-and degree of apraxia severity, as measured by the AOS feature variable group. CONCLUSIONS Quantitative features reveal heterogeneity of MSI in the 4RT group in terms of both overall severity and subtype of MSI. Results suggest the potential for acoustic and kinematic speech assessment methods to inform characterization of motor speech impairment in 4RT-associated syndromes. SUPPLEMENTAL MATERIAL https://doi.org/10.23641/asha.21401778.
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Affiliation(s)
- Claire Cordella
- Department of Speech, Language & Hearing Sciences, Boston University, MA
| | - Sarah E. Gutz
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, MA
| | - Marziye Eshghi
- Department of Communication Sciences and Disorders, MGH Institute of Health Professions, Boston, MA
| | - Kaila L. Stipancic
- Department of Communicative Disorders and Sciences, University at Buffalo, NY
| | - Megan Schliep
- Department of Communication Sciences and Disorders, MGH Institute of Health Professions, Boston, MA
| | | | - Jordan R. Green
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, MA
- Department of Communication Sciences and Disorders, MGH Institute of Health Professions, Boston, MA
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Ngo QC, Motin MA, Pah ND, Drotár P, Kempster P, Kumar D. Computerized analysis of speech and voice for Parkinson's disease: A systematic review. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022; 226:107133. [PMID: 36183641 DOI: 10.1016/j.cmpb.2022.107133] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Revised: 09/13/2022] [Accepted: 09/13/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND AND OBJECTIVE Speech impairment is an early symptom of Parkinson's disease (PD). This study has summarized the literature related to speech and voice in detecting PD and assessing its severity. METHODS A systematic review of the literature from 2010 to 2021 to investigate analysis methods and signal features. The keywords "Automatic analysis" in conjunction with "PD speech" or "PD voice" were used, and the PubMed and ScienceDirect databases were searched. A total of 838 papers were found on the first run, of which 189 were selected. One hundred and forty-seven were found to be suitable for the review. The different datasets, recording protocols, signal analysis methods and features that were reported are listed. Values of the features that separate PD patients from healthy controls were tabulated. Finally, the barriers that limit the wide use of computerized speech analysis are discussed. RESULTS Speech and voice may be valuable markers for PD. However, large differences between the datasets make it difficult to compare different studies. In addition, speech analytic methods that are not informed by physiological understanding may alienate clinicians. CONCLUSIONS The potential usefulness of speech and voice for the detection and assessment of PD is confirmed by evidence from the classification and correlation results.
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Affiliation(s)
| | - Mohammod Abdul Motin
- Biosignals Lab, RMIT University, Melbourne, Australia; Department of Electrical & Electronic Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh
| | - Nemuel Daniel Pah
- Biosignals Lab, RMIT University, Melbourne, Australia; Universitas Surabaya, Indonesia
| | - Peter Drotár
- Intelligent Information Systems Lab, Technical University of Kosice, Letna 9, 42001, Kosice, Slovakia
| | - Peter Kempster
- Neurosciences Department, Monash Health, Clayton, VIC, Australia; Department of Medicine, School of Clinical Sciences, Monash University, Clayton, VIC, Australia
| | - Dinesh Kumar
- Biosignals Lab, RMIT University, Melbourne, Australia.
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