Speech disorders in Parkinson’s disease: early diagnostics and effects of medication and brain stimulation

Abstract

Hypokinetic dysarthria (HD) occurs in 90% of Parkinson’s disease (PD) patients. It manifests specifically in the areas of articulation, phonation, prosody, speech fluency, and faciokinesis. We aimed to systematically review papers on HD in PD with a special focus on (1) early PD diagnosis and monitoring of the disease progression using acoustic voice and speech analysis, and (2) functional imaging studies exploring neural correlates of HD in PD, and (3) clinical studies using acoustic analysis to evaluate effects of dopaminergic medication and brain stimulation. A systematic literature search of articles written in English before March 2016 was conducted in the Web of Science, PubMed, SpringerLink, and IEEE Xplore databases using and combining specific relevant keywords. Articles were categorized into three groups: (1) articles focused on neural correlates of HD in PD using functional imaging (n = 13); (2) articles dealing with the acoustic analysis of HD in PD (n = 52); and (3) articles concerning specifically dopaminergic and brain stimulation-related effects as assessed by acoustic analysis (n = 31); the groups were then reviewed. We identified 14 combinations of speech tasks and acoustic features that can be recommended for use in describing the main features of HD in PD. While only a few acoustic parameters correlate with limb motor symptoms and can be partially relieved by dopaminergic medication, HD in PD seems to be mainly related to non-dopaminergic deficits and associated particularly with non-motor symptoms. Future studies should combine non-invasive brain stimulation with voice behavior approaches to achieve the best treatment effects by enhancing auditory-motor integration.

This is a preview of subscription content, log in to check access.

References

  1. Ahn JS, Sidtis DVL, Sidtis JJ (2014) Effects of deep brain stimulation on pausing during spontaneous speech in Parkinson’s disease. J Med Speech Lang Pathol 21:179–186. doi:10.1016/j.rasd.2014.08.015

    PubMed  PubMed Central  Google Scholar 

  2. Arnold C, Gehrig J, Gispert S et al (2014) Pathomechanisms and compensatory efforts related to Parkinsonian speech. Neuroimage Clin 4:82–97. doi:10.1016/j.nicl.2013.10.016

    PubMed  Article  Google Scholar 

  3. Arora S, Venkataraman V, Zhan A, Donohue S, Biglan KM, Dorsey ER, Little MA (2015) Detecting and monitoring the symptoms of Parkinson’s disease using smartphones: a pilot study. Parkinsonism Relat Disord 21(6):650–653

    CAS  PubMed  Article  Google Scholar 

  4. Asgari A, Shafran I (2010) Extracting cues from speech for predicting severity of Parkinson’s disease. In: International Workshop on Machine Learning for Signal Processing (MLSP 2010), pp 462–467

  5. Aström F, Koker R (2011) A parallel neural network approach to prediction of Parkinson’s Disease. Expert Syst Appl 38(10):12470–12474

    Article  Google Scholar 

  6. Atkinson-Clement C, Sadat J, Pinto S (2015) Behavioral treatments for speech in Parkinson’s disease: meta-analyses and review of the literature. Neurodegener Dis Manag 5(3):233–248

    PubMed  Article  Google Scholar 

  7. Bakar ZA, Ibrahim NF, Sahak R, Tahir NM (2012) Parkinson’s disease feature subset selection based on voice samples. In: 2012 IEEE Symposium on Computer Applications and Industrial Electronics (ISCAIE), Kota Kinabalu, pp 163–166

  8. Baker KK, Ramig LO, Luschei ES, Smith ME (1998) Thyroarytenoid muscle activity associated with hypophonia in Parkinson’s disease and aging. Neurology 51:1592–1598

    CAS  PubMed  Article  Google Scholar 

  9. Bandini A, Giovannelli F, Orlandi S, Barbagallo S, Cincotta M, Vanni P, Chiaramonti R, Borgheresi A, Zaccara G, Manfredi C (2015) Automatic identification of dysprosody in idiopathic parkinson’s disease. Biomed Signal Process Control 17:47–54

    Article  Google Scholar 

  10. Bayestehtashk A, Asgari M, Shafran I, McNames J (2015) Fully automated assessment of the severity of Parkinson’s Disease from speech. Comput Speech Lang 29(1):172–185

    PubMed  Article  Google Scholar 

  11. Belalcazar-Bolaños EA, Orozco-Arroyave JR, Arias-Londoño JD, Vargas-Bonilla JF, Nöth E (2013a) Automatic detection of Parkinson’s disease using noise measures of speech. In: Image, Signal Processing, and Artificial Vision (STSIVA), 2013 XVIII Symposium of, Bogota, pp 1–5

  12. Belalcázar-Bolaños EA, Orozco-Arroyave JR, Vargas-Bonilla JF, Arias-Londoño JD, Castellanos-Domínguez CG, Nöth E (2013b) New Cues in Low-Frequency of Speech for Automatic Detection of Parkinson’s Disease. In José Manuel Ferrández de Vicente, José Ramón Álvarez Sánchez, Félix de la Paz López, Javier Toledo-Moreo, F (eds) ‘IWINAC (1)’. Springer, pp 283–292

  13. Benba A, Jilbab A, Hammouch A, Sandabad S (2015) Voiceprints analysis using MFCC and SVM for detecting patients with Parkinson’s disease. In: 2015 International Conference on Electrical and Information Technologies (ICEIT), Marrakech, pp 300–304

  14. Berg E, Björnram C, Hartelius L, Laakso K, Johnels B (2003) High-level language difficulties in parkinson’s disease. Clin Linguist Phon 17:63–80

    PubMed  Article  Google Scholar 

  15. Berg D, Postuma RB, Adler CH et al (2015) MDS research criteria for prodromal Parkinson’s disease. Mov Disord 30:1600–1611. doi:10.1002/mds.26431

    PubMed  Article  Google Scholar 

  16. Bocklet T, Nöth E, Stemmer G, Ruzickova H, Rusz J (2011) Detection of persons with Parkinson’s disease by acoustic, vocal, and prosodic analysis. In: 2011 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), Waikoloa, HI, pp 478–483

  17. Cantiniaux S, Vaugoyeau M, Robert D, Horrelou-Pitek C, Mancini J, Witjas T, Azulay JP (2010) Comparative analysis of gait and speech in Parkinson’s disease: hypokinetic or dysrhythmic disorders? J Neurol Neurosurg Psychiatry 81(2):177–184

    PubMed  Article  Google Scholar 

  18. Chenausky K, Macauslan J, Goldhor R (2011) Acoustic analysis of PD speech. Parkinsons Dis 2011:435232. doi:10.4061/2011/435232

    PubMed  PubMed Central  Google Scholar 

  19. Chou Y, Hickey PT, Sundman M et al (2015) Effects of repetitive transcranial magnetic stimulation on motor symptoms in Parkinson disease: a systematic review and meta-analysis. JAMA Neurol 72:432–440. doi:10.1001/jamaneurol.2014.4380

    PubMed  PubMed Central  Article  Google Scholar 

  20. D’Alatri L, Paludetti G, Contarino MF et al (2008) Effects of bilateral subthalamic nucleus stimulation and medication on parkinsonian speech impairment. J Voice 22:365–372. doi:10.1016/j.jvoice.2006.10.010

    PubMed  Article  Google Scholar 

  21. Darley FL, Aronson AE, Brown JR (1969a) Differential diagnostic patterns of dysarthria. J Speech Hear Res 12:246–269

    CAS  PubMed  Article  Google Scholar 

  22. Darley FL, Aronson AE, Brown JR (1969b) Clusters of deviant speech dimensions in the dysarthrias. J Speech Hear Res 12:462–496

    CAS  PubMed  Article  Google Scholar 

  23. Dias AE, Barbosa ER, Coracini K et al (2006) Effects of repetitive transcranial magnetic stimulation on voice and speech in Parkinson’s disease. Acta Neurol Scand 113:92–99. doi:10.1111/j.1600-0404.2005.00558.x

    CAS  PubMed  Article  Google Scholar 

  24. Dromey C, Bjarnason S (2011) A preliminary report on disordered speech with deep brain stimulation in individuals with Parkinson’s disease. Parkinsons Dis 2011:1–11. doi:10.4061/2011/796205

    Article  Google Scholar 

  25. Dromey C, Kumar R, Lang AE, Lozano AM (2000) An investigation of the effects of subthalamic nucleus stimulation on acoustic measures of voice. Mov Disord 15:1132–1138

    CAS  PubMed  Article  Google Scholar 

  26. Duffy JR, Strand EA, Clark H et al (2015) Primary progressive apraxia of speech: clinical features and acoustic and neurologic correlates. Am J Speech Lang Pathol 24:88–100. doi:10.1044/2015_AJSLP-14-0174

    PubMed  PubMed Central  Article  Google Scholar 

  27. Eickhoff SB, Heim S, Zilles K, Amunts K (2009) A systems perspective on the effective connectivity of overt speech production. Philos Trans R Soc A Math Phys Eng Sci 367:2399–2421

    Article  Google Scholar 

  28. Elfmarkova N, Gajdos M, Mrackova M, Mekyska J, Mikl M, Rektorova I (2016) Impact of Parkinson’s disease and levodopa on resting state functional connection related to speech prosody control. Parkinsonism Relat Disord 22(Suppl 1):S52–S55

    PubMed  Article  Google Scholar 

  29. Eliasova I, Mekyska J, Kostalova M, Marecek R, Smekal Z, Rektorova I (2013) Acoustic evaluation of short-term effects of repetitive transcranial magnetic stimulation on motor aspects of speech in Parkinson’s disease. J Neural Transm 120(4):597–605

    CAS  PubMed  Article  Google Scholar 

  30. Eskidere O, Ertac F, Hanilci C (2012) A comparison of regression methods for remote tracking of Parkinson’s disease progression. Expert Syst Appl 39(5):5523–5528

    Article  Google Scholar 

  31. Fahn S, Elton RL (1987) Unified Parkinson’s Disease Rating Scale. In: Fahn S, Marsden CD, Calne DB, Goldstein M (eds) Recent developments in Parkinson’s disease. Macmillan Health Care Information, New Jersey, pp 153–163

    Google Scholar 

  32. Fisher E, Goberman AM (2010) Voice onset time in Parkinson disease. J Commun Disord 43:21–34

    Article  Google Scholar 

  33. Flasskamp A, Kotz SA, Schlegel U, Skodda S (2012) Acceleration of syllable repetition in Parkinson’s disease is more prominent in the left-side dominant patients. Parkinsonism Relat Disord 18(4):343–347

    PubMed  Article  Google Scholar 

  34. Forrest K, Weismer G, Turner G (1989) Kinematic, acoustic and perceptual analyses of connected speech produced by Parkinsonian and normalgeriatric males. J Acoust Soc Am 85:2608–2622

    CAS  PubMed  Article  Google Scholar 

  35. Fujii S, Wan CY (2014) The role of rhythm in speech and language rehabilitation: the SEP hypothesis. Front Hum Neurosci 8:777. doi:10.3389/fnhum.2014.00777

    PubMed  PubMed Central  Google Scholar 

  36. Galaz Z, Mekyska J, Mzourek Z, Smekal Z, Rektorova I, Eliasova I, Kostalova M, Mrackova M, Berankova D (2016) Prosodic analysis of neutral, stress-modified and rhymed speech in patients with Parkinson’s disease. Comput Methods Programs Biomed. doi:10.1016/j.cmpb.2015.12.011 in press

    PubMed  Google Scholar 

  37. Gelzinis A, Verikas A, Bacauskiene M (2008) Automated speech analysis applied to laryngeal disease categorization. Comput Methods Program Biomed 91(1):36–47

    CAS  Article  Google Scholar 

  38. Gentil M, Pollak P, Perret J (1995) Parkinsonian dysarthria. Rev Neurol 151:105–112

    CAS  PubMed  Google Scholar 

  39. Gentil M, Chauvin P, Pinto S et al (2001) Effect of bilateral stimulation of the subthalamic nucleus on Parkinsonian voice. Brain Lang 78:233–240. doi:10.1006/brln.2001.2466

    CAS  PubMed  Article  Google Scholar 

  40. Gentil M, Pinto S, Pollak P, Benabid A-L (2003) Effect of bilateral stimulation of the subthalamic nucleus on parkinsonian dysarthria. Brain Lang 85:190–196

    PubMed  Article  Google Scholar 

  41. Hall D, Ouyang B, Lonnquist E, Newcombe J (2011) Pragmatic communication is impaired in Parkinson disease. Int J Neurosci 121:254–256

    PubMed  Article  Google Scholar 

  42. Hariharan M, Polat K, Sindhu R (2014) A new hybrid intelligent system for accurate detection of Parkinson’s disease. Comput Methods Program Biomed 113(3):904–913

    CAS  Article  Google Scholar 

  43. Hartelius L, Svantesson P, Hedlund A (2010) Short-term effects of repetitive transcranial magnetic stimulation on speech and voice in individuals with Parkinson’s disease. Folia Phoniatr Logop 62:104–109. doi:10.1159/000287208

    CAS  PubMed  Article  Google Scholar 

  44. Hazan H, Hilu D, Manevitz L, Ramig LO, Sapir S (2012) Early diagnosis of Parkinson’s disease via machine learning on speech data. In: 2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel (IEEEI), Eilat, pp 1–4

  45. Henriquez P, Alonso J, Ferrer M, Travieso C, Godino-Llorente J, Diaz-de-Maria F (2009) Characterization of healthy and pathological voice through measures based on nonlinear dynamics. IEEE T Audio Speech 17(6):1186–1195

    Article  Google Scholar 

  46. Herrington TM, Cheng JJ, Eskandar EN (2016) Mechanisms of deep brain stimulation. J Neurophysiol 115:19–38. doi:10.1152/jn.00281.2015

    PubMed  Article  Google Scholar 

  47. Hickok G, Poeppel D (2007) The cortical organization of speech processing. Nat Rev Neurosci 8:393–402. doi:10.1038/nrn2113

    CAS  PubMed  Article  Google Scholar 

  48. Hillenbrand J, Houde RA (1996) Acoustic correlates of breathy vocal quality: dysphonic voices and continuous speech. J Speech Hear Res 39(2):311–321

    CAS  PubMed  Article  Google Scholar 

  49. Ho AK, Iansek R, Marigliani C, Bradshaw JL, Gates S (1999) Speech impairment in a large sample of patients with Parkinson’s disease. J Behav Neurol 11:131–137

    CAS  Article  Google Scholar 

  50. Hornykiewicz O (1998) Biochemical aspects of Parkinson’s disease. Neurology 51:S2–S9

    CAS  PubMed  Article  Google Scholar 

  51. Huh YE, Park J, Suh MK, Lee SE, Kim J et al (2015) Differences in early speech patterns between Parkinson variant of multiple system atrophy and Parkinson’s disease. Brain Lang 147:14–20

    PubMed  Article  Google Scholar 

  52. Kasuya H, Ogawa S, Mashima K, Ebihara S (1986) Normalized noise energy as an acoustic measure to evaluate pathologic voice. J Acoust Soc Am 80(5):1329–1334

    CAS  PubMed  Article  Google Scholar 

  53. Kegl J, Cohen H, Poizner H (1999) Articulatory consequences of Parkinson’s Disease: perspectives from two modalities. Brain Cogn 40:355–386

    CAS  PubMed  Article  Google Scholar 

  54. Kim Y, Choi Y (2016) A cross-linguistic approach to speech intelligibility in people with PD. Mov Disord 31 (suppl 2). http://www.mdsabstracts.org/abstract/a-cross-linguistic-approach-to-speech-intelligibilityin-people-with-pd/. Accessed 11 Jan 2017 .

  55. Kim Y, Kent RD, Weismer G (2011) An acoustic study of the relationships among neurologic disease, dysarthria type, and severity of dysarthria. J Speech Lang Hear Res 54(2):417–429

    PubMed  Article  Google Scholar 

  56. Klostermann F, Ehlen F, Vesper J et al (2008) Effects of subthalamic deep brain stimulation on dysarthrophonia in Parkinson’s disease. J Neurol Neurosurg Psychiatry 79:522–529. doi:10.1136/jnnp.2007.123323

    CAS  PubMed  Article  Google Scholar 

  57. Kostalova M, Mrackova M, Marecek R, Berankova D, Eliasova I et al (2013) The 3F test dysarthric profile—normative speech values in Czech. Cesk Slov Neurol N 76/109(5):614–618

    Google Scholar 

  58. Lee VS, Zhou XP, Rahn DA et al (2008) Perturbation and nonlinear dynamic analysis of acoustic phonatory signal in Parkinsonian patients receiving deep brain stimulation. J Commun Disord 41:485–500. doi:10.1016/j.jcomdis.2008.02.001

    PubMed  PubMed Central  Article  Google Scholar 

  59. Lefaucheur J-P, André-Obadia N, Antal A et al (2014) Evidence-based guidelines on the therapeutic use of repetitive transcranial magnetic stimulation (rTMS). Clin Neurophysiol 125:2150–2206. doi:10.1016/j.clinph.2014.05.021

    PubMed  Article  Google Scholar 

  60. Liotti M, Ramig LO, Vogel D et al (2003) Hypophonia in Parkinson’s disease neural correlates of voice treatment revealed by PET. Neurology 60:432–440. doi:10.1212/WNL.60.3.432

    CAS  PubMed  Article  Google Scholar 

  61. Liss JM, LeGendre S, Lotto AJ (2010) Discriminating dysarthria type from envelope modulation spectra. J Speech Lang Hear Res 53(5):1246–1255

    PubMed  PubMed Central  Article  Google Scholar 

  62. Little MA, Mcsharry PE, Roberts SJ, Costello DAE, Moroz IM (2007) Exploiting nonlinear recurrence and fractal scaling properties for voice disorder detection. Biomed Eng Online 6:23

    PubMed  PubMed Central  Article  Google Scholar 

  63. Little MA, Mcsharry PE, Hunter E, Spielman J, Ramig LO (2009) Suitability of dysphonia measurements for telemonitoring of Parkinson’s disease. IEEE T Biomed Eng 56(4):1015–1022

    Article  Google Scholar 

  64. Lowit A (2008) Quantification of rhythm problems in disordered speech: a re-evaluation. Philos Trans R Soc Lond B Biol Sci 19/369(1658):20130404

    Google Scholar 

  65. Maillet A, Krainik A, Debû B et al (2012) Levodopa effects on hand and speech movements in patients with Parkinson’s disease: a FMRI study. PLoS One 7:e46541. doi:10.1371/journal.pone.0046541

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  66. Mate MA, Cobeta I, Jiménez-Jiménez FJ, Figueiras R (2012) Digital voice analysis in patients with advanced Parkinson’s disease undergoing deep brain stimulation therapy. J Voice 26:496–501. doi:10.1016/j.jvoice.2011.03.006

    PubMed  Article  Google Scholar 

  67. Mekyska J, Smekal Z, Kostalova M, Mrackova M, Skutilova S, Rektorova I (2011) Motor aspects of speech impairment in Parkinson’s disease and their assessment. Cesk Slov Neurol N 74/107(6):662–668

    Google Scholar 

  68. Mekyska J, Galaz Z, Mzourek Z, Smekal Z, Rektorova I, et al. (2015a) Assessing Progress of Parkinson’s Disease Using Acoustic Analysis of Phonation. In: International Work Conference on Bioinspired Intelligence (IWOBI 2015), pp 115–122

  69. Mekyska J, Janousova E, Gomez-Vilda P, Smekal Z, Rektorova I et al (2015b) Robust and complex approach of pathological speech signal analysis. Neurocomputing 167(1):94–111

    Article  Google Scholar 

  70. Mekyska J, Smekal Z, Galaz Z, Mzourek Z, Rektorova I et al (2016) Perceptual features as markers of Parkinson’s Disease: the issue of clinical interpretability. In: Esposito A, Faundez-Zanuy M, Esposito AM, Cordasco G, Casals JS et al (eds) Recent advances in nonlinear speech processing. Springer International Publishing, New York, pp 83–91

    Google Scholar 

  71. Michaelis D, Gramss T, Strube HW (1997) Glottal-to-noise excitation ratio—a new measure for describing pathological voices. Acta Acust United Acust 83(4):700–706

    Google Scholar 

  72. Midi I, Dogan M, Koseoglu M, Can G, Sehitoglu MA et al (2008) Voice abnormalities and their relation with motor dysfunction in Parkinson’s disease. Acta Neurol Scand 117(1):26–34

    CAS  PubMed  Google Scholar 

  73. Moers C, Möbius B, Rosanowski F, Nöth E, Eysholdt U, Haderlein T (2012) Vowel- and text-based cepstral analysis of chronic hoarseness. J Voice 26(4):416–424

    PubMed  Article  Google Scholar 

  74. Moreau C, Ozsancak C, Blatt JL, Derambure P, Destee A, Defebvre L (2007) Oral festination in Parkinson’s disease: biomechanical analysis and correlation with festination and freezing of gait. Mov Disord 22(10):1503–1506

    PubMed  Article  Google Scholar 

  75. Moreau C, Pennel-Ployart O, Pinto S et al (2011) Modulation of dysarthropneumophonia by low-frequency STN DBS in advanced Parkinson’s disease. Mov Disord 26:659–663. doi:10.1002/mds.23538

    PubMed  Article  Google Scholar 

  76. Moretti R, Torre P, Antonello RM, Capus L, Gioulis M, Zambito Marsala S, Cazzato G, Bava A (2003) Speech initiation hesitation following subthalamic nucleus stimulation in a patient with parkinson’s disease. Eur Neurol 49:251–253

    CAS  PubMed  Article  Google Scholar 

  77. Mouffak A, Belbachir MF (2012) Non-causal recursive digital filters in multi-band dysperiodicity analysis of synthetic simple vowels. In: 2012 6th International Conference on Sciences of Electronics, Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), Sousse, pp 792–796

  78. Murdoch BE, Ng ML, Barwood CHS (2012) Treatment of articulatory dysfunction in Parkinson’s disease using repetitive transcranial magnetic stimulation. Eur J Neurol 19:340–347. doi:10.1111/j.1468-1331.2011.03524.x

    CAS  PubMed  Article  Google Scholar 

  79. Musa P, Baha S, Delen D (2015) Computer-aided diagnosis of Parkinson’s disease using complex-valued neural networks and mRMR feature selection algorithm. J Healthc Eng 6(3):281–302

    Article  Google Scholar 

  80. Naranjo L, Pérez CJ, Campos-Roca Y, Martín J (2016) Addressing voice recording replications for Parkinson’s disease detection. Expert Syst Appl 46:286–292

    Article  Google Scholar 

  81. Narayana S, Jacks A, Robin DA et al (2009) A noninvasive imaging approach to understanding speech changes following deep brain stimulation in Parkinson’s disease. Am J Speech Lang Pathol 18:146. doi:10.1044/1058-0360(2008/08-0004)

    PubMed  Article  Google Scholar 

  82. Narayana S, Fox PT, Zhang W et al (2010) Neural correlates of efficacy of voice therapy in Parkinson’s disease identified by performance-correlation analysis. Hum Brain Mapp 31:222–236. doi:10.1002/hbm.20859

    PubMed  PubMed Central  Google Scholar 

  83. New AB, Robin DA, Parkinson AL et al (2015) The intrinsic resting state voice network in Parkinson’s disease. Hum Brain Mapp 36:1951–1962. doi:10.1002/hbm.22748

    PubMed  PubMed Central  Article  Google Scholar 

  84. Novotny M, Rusz J, Cmejla R, Ruzicka E (2014) Automatic evaluation of articulatory disorders in Parkinson’s disease. IEEE/ACM T Audio Speech Lang Process 22:1366–1378

    Article  Google Scholar 

  85. Okun MS (2012) Deep-brain stimulation for Parkinson’s disease. N Engl J Med 367:1529–1538. doi:10.1056/NEJMct1208070

    CAS  PubMed  Article  Google Scholar 

  86. Orozco-Arroyave J, Arias-Londoño JD, Vargas-Bonilla JF, Nöth E (2013a) Analysis of speech from people with Parkinson’s disease through nonlinear dynamics. Lect Notes Artif Intell 7911:112–119

    Google Scholar 

  87. Orozco-Arroyave J.R., Arias-Londoño J.D., Vargas-Bonilla J.F., Nöth E. (2013b) Perceptual Analysis of Speech Signals from People with Parkinson’s Disease. In: Ferrández Vicente J.M., Álvarez Sánchez J.R., de la Paz López F., Toledo Moreo F.J. (eds) Natural and Artificial Models in Computation and Biology. IWINAC 2013. Lecture Notes in Computer Science, vol 7930. Springer, Berlin, Heidelberg

  88. Orozco-Arroyave JR, Hönig F, Arias-Londoño JD, Vargas-Bonilla JF, Skodda S, Rusz J, Nöth E (2014a) Automatic detection of Parkinson’s disease from words uttered in three different languages. In: Proceedings of the 15th Annual Conference of the International Speech Communication Association (INTERSPEECH), Singapore, pp 1573–1577

  89. Orozco-Arroyave JR, Belalcázar-Bolaños EA, Arias-Londoño JD, Vargas-Bonilla JF, Haderlein T, Nöth E (2014b) Phonation and articulation analysis of spanish vowels for automatic detection of Parkinson’s disease. Lecture notes in artificial intelligence, vol 8655. Springer, pp 389–296

  90. Orozco-Arroyave JR, Hönig F, Arias-Londoño JD, Vargas-Bonilla JF, Skodda S, Rusz J, Nöth E (2015b) Voiced/unvoiced transitions in speech as a potential bio-marker to detect Parkinson’s disease. In: Proceedings of 16th INTERSPEECH, Dresden, Germany, pp 95–99

  91. Orozco-Arroyave JR, Hönig F, Arias-Londoño JD, Vargas-Bonilla JF, Daqrouq K, Skodda S, Rusz J, Nöth E (2016) Automatic detection of Parkinson’s disease in running speech spoken in three different languages. J Acoust Soc Am 139(1):481–500

    CAS  PubMed  Article  Google Scholar 

  92. Park HK, Yoo JY, Kwon M, Lee JH, Lee SJ, Kim SR, Kim MJ, Lee MC, Lee SM, Chung SJ (2013) Gait freezing and speech disturbance in Parkinson’s disease. Neurol Sci 35(3):357–363

    PubMed  Article  Google Scholar 

  93. Pell MD, Cheang HS, Leonard CL (2006) The impact of parkinson’s disease on vocal-prosodic communication from the perspective of listeners. Brain Lang 97:123–134

    PubMed  Article  Google Scholar 

  94. Peterek T, Dohnalek P, Gajdos P, Smondrk M (2013) Performance evaluation of Random Forest regression model in tracking Parkinson’s disease progress. In: 13th International Conference on Hybrid Intelligent Systems (HIS 2013), pp 83–87

  95. Pinto S, Ozsancak C, Tripoliti E et al (2004a) Treatments for dysarthria in Parkinson’s disease. Lancet Neurol 3:547–556. doi:10.1016/S1474-4422(04)00854-3

    PubMed  Article  Google Scholar 

  96. Pinto S, Thobois S, Costes N et al (2004b) Subthalamic nucleus stimulation and dysarthria in Parkinson’s disease: a PET study. Brain 127:602–615. doi:10.1093/brain/awh074

    PubMed  Article  Google Scholar 

  97. Pinto S, Gentil M, Krack P et al (2005) Changes induced by levodopa and subthalamic nucleus stimulation on parkinsonian speech. Mov Disord 20:1507–1515. doi:10.1002/mds.20601

    PubMed  Article  Google Scholar 

  98. Pinto S, Mancini L, Jahanshahi M et al (2011) Functional magnetic resonance imaging exploration of combined hand and speech movements in Parkinson’s disease. Mov Disord 26:2212–2219. doi:10.1002/mds.23799

    PubMed  PubMed Central  Article  Google Scholar 

  99. Pinto S, Ferraye M, Espesser R et al (2014) Stimulation of the pedunculopontine nucleus area in Parkinson’s disease: effects on speech and intelligibility. Brain 137:2759–2772. doi:10.1093/brain/awu209

    PubMed  Article  Google Scholar 

  100. Pinto S, Cardoso R, Sadat J et al (2016) Dysarthria in individuals with Parkinson’s disease: a protocol for a binational, cross-sectional, case-controlled study in French and European Portuguese (FraLusoPark). BMJ Open 6:e012885

    PubMed  PubMed Central  Article  Google Scholar 

  101. Postuma R, Lang AE, Gagnon JF, Pelletier A, Montplaisir JY (2012) How does parkinsonism start? Prodromal parkinsonism motor changes in idiopathic REM sleep behaviour disorder. Brain 35(Pt 6):1860–1870

    Article  Google Scholar 

  102. Postuma RB, Berg D, Stern M et al (2015) MDS clinical diagnostic criteria for Parkinson’s disease. Mov Disord 30:1591–1601. doi:10.1002/mds.26424

    PubMed  Article  Google Scholar 

  103. Pützer M, Barry WJ, Moringlane JR (2008) Effect of bilateral stimulation of the subthalamic nucleus on different speech subsystems in patients with Parkinson’s disease. Clin Linguist Phon 22:957–973. doi:10.1080/02699200802394823

    PubMed  Article  Google Scholar 

  104. Rektorova I, Barrett J, Mikl M et al (2007) Functional abnormalities in the primary orofacial sensorimotor cortex during speech in Parkinson’s disease. Mov Disord 22:2043–2051. doi:10.1002/mds.21548

    PubMed  Article  Google Scholar 

  105. Rektorova I, Mikl M, Barrett J et al (2012) Functional neuroanatomy of vocalization in patients with Parkinson’s disease. J Neurol Sci 313:7–12. doi:10.1016/j.jns.2011.10.020

    CAS  PubMed  Article  Google Scholar 

  106. Riecker A, Kassubek J, Gröschel K, et al (2006) The cerebral control of speech tempo: Opposite relationship between speaking rate and BOLD signal changes at striatal and cerebellar structures. Neuroimage 29:46–53. doi:10.1007/s00702-017-1676-0

  107. Roy N, Nissen SL, Dromey C, Sapir S (2009) Articulatory changes in muscle tension dysphonia: evidence of vowel space expansion following manual circumlaryngeal therapy. J Commun Disord 42:124–135

    PubMed  Article  Google Scholar 

  108. Rusz J, Cmejla R, Ruzickova H, Ruzicka E (2011) Quantitative acoustic measurements for characterization of speech and voice disorders in early untreated Parkinson’s disease. J Acoust Soc Am 129:350–367

    CAS  PubMed  Article  Google Scholar 

  109. Rusz J, Cmejla R, Ruzickova H, Klempir J, Majerova V, Picmausova J, Roth J, Ruzicka E (2013a) Evaluation of speech impairment in early stages of parkinson’s disease: a prospective study with the role of pharmacotherapy. J Neural Transm 120:319–329

    CAS  PubMed  Article  Google Scholar 

  110. Rusz J, Cmejla R, Tykalova T, Ruzickova H, Klempir J, Majerova V, Picmausova J, Roth J, Ruzicka E (2013b) Imprecise vowel articulation as a potential early marker of Parkinson’s disease: effect of speaking task. J Acoust Soc Am 134:2171–2181

    PubMed  Article  Google Scholar 

  111. Rusz J, Bonnet C, Klempir J, Tykalova T, Baborova E et al (2015) Speech disorders reflect differing pathophysiology in Parkinson’s disease, progressive supranuclear palsy and multiple system atrophy. J Neurol 262(4):992–1001

    CAS  PubMed  Article  Google Scholar 

  112. Rusz J, Tykalová T, Klempíř J et al (2016a) Effects of dopaminergic replacement therapy on motor speech disorders in Parkinson’s disease: longitudinal follow-up study on previously untreated patients. J Neural Transm 123:379–387. doi:10.1007/s00702-016-1515-8

    CAS  PubMed  Article  Google Scholar 

  113. Rusz J, Hlavnicka J, Tykalova T, Buskova J, Ulmanova O, Ruzicka E, Sonka K (2016b) Quantitative assessment of motor speech abnormalities in idiopathic rapid eye movement sleep behaviour disorder. Sleep Med 19:141–147

    PubMed  Article  Google Scholar 

  114. Rusz J, Novotny M, Hlavnicka J, Tykalova T, Ruzicka E (2016c) High-accuracy voice-based classification between patients with Parkinson’s disease and other neurological diseases may be an easy task with inappropriate experimental design. IEEE Trans Neural Syst Rehabil Eng. doi:10.1109/TNSRE.2016.262188 in press

    Google Scholar 

  115. Sachin S, Senthil Kumaran S, Singh S et al (2008) Functional mapping in PD and PSP for sustained phonation and phoneme tasks. J Neurol Sci 273:51–56. doi:10.1016/j.jns.2008.06.024

    CAS  PubMed  Article  Google Scholar 

  116. Sakar CO, Kursun O (2009) Telediagnosis of Parkinson’s disease using measurements of dysphonia. J Med Syst 34(4):591–599

    PubMed  Article  Google Scholar 

  117. Sakar BE, Isenkul ME, Sakar CO, Sertbas A, Gurgen F, Delil S, Apaydin H, Kursun O (2013) Collection and analysis of a Parkinson speech dataset with multiple types of sound recordings. IEEE J Biomed Health Inform 17(4):828–834

    PubMed  Article  Google Scholar 

  118. Santos LLM, Dos Reis LO, Bassi I et al (2010) Acoustic and hearing-perceptual voice analysis in individuals with idiopathic Parkinson’s disease in “on” and “off” stages. Arq Neuropsiquiatr 68:706–711. doi:10.1590/S0004-282X2010000500006

    PubMed  Article  Google Scholar 

  119. Sapir S, Ramig LO, Spielman JL, Fox C (2010) Formant centralization ratio: a proposal for a new acoustic measure of dysarthric speech. J Speech Lang Hear Res 53:1–20

    Article  Google Scholar 

  120. Sauvageau VM, Macoir J, Langlois M et al (2014) Changes in vowel articulation with subthalamic nucleus deep brain stimulation in dysarthric speakers with parkinson’s disease. Parkinsons Dis. doi:10.1155/2014/487035

    Google Scholar 

  121. Sauvageau VM, Roy JP, Cantin L et al (2015) Articulatory changes in vowel production following STN DBS and levodopa intake in Parkinson’s disease. Parkinsons Dis. doi:10.1155/2015/382320

    Google Scholar 

  122. Saxena M, Behari M, Kumaran SS, Goyal V, Narang V (2014) Assessing speech dysfunction using BOLD and acoustic analysis in parkinsonism. Parkinsonism Relat D 20(8):855–861

    Article  Google Scholar 

  123. Schmitz-Hubsch T, Eckert O, Schlegel U, Klockgether T, Skodda S (2012) Instability of syllable repetition in patients with spinocerebellar ataxia and Parkinson’s disease. Mov Disord 27(2):316–319

    PubMed  Article  Google Scholar 

  124. Schulz GM, Grant MK (2000) Effects of speech therapy and pharmacologic and surgical treatments on voice and speech in Parkinson’s disease: a review of the literature. J Commun Disord 33:59–88

    CAS  PubMed  Article  Google Scholar 

  125. Shahbakhti M, Taherifar D, Zareei Z (2013a) Combination of PCA and SVM for diagnosis of Parkinson’s disease. In: 2013 2nd International Conference on Advances in Biomedical Engineering (ICABME), Tripoli, pp 137–140

  126. Shahbakhti M, Taherifar D, Sorouri A (2013b) Linear and non-linear speech features for detection of Parkinson’s disease. In: 2013 6th Biomedical Engineering International Conference (BMEiCON), Amphur Muang, pp 1–3

  127. Shao J, Maccallum JK, Zhang Y, Sprecher A, Jiang JJ (2010) Acoustic analysis of the tremulous voice: assessing the utility of the correlation dimension and perturbation parameters. J Commun Disord 43:35–44

    PubMed  Article  Google Scholar 

  128. Shirvan RA, Tahami E (2011) Voice analysis for detecting Parkinson’s disease using genetic algorithm and KNN classification method. In: 2011 18th Iranian Conference of Biomedical Engineering (ICBME), Tehran, pp 278–283

  129. Silva DG, Oliveira LC, Andrea M (2009) Jitter estimation algorithms for detection of pathological voices. EURASIP J Adv Signal Process 2009:1–9

  130. Sidtis DVL, Rogers T, Godier V et al (2010) Voice and fluency changes as a function of speech task and deep brain stimulation. J Speech Lang Hear Res 53:1167. doi:10.1044/1092-4388(2010/09-0154)

    PubMed  PubMed Central  Article  Google Scholar 

  131. Siebner HR (2005) Treatment of Movement Disorders. In: Hallett M, Chokroverty S (eds) Magnetic stimulation in clinical neurophysiology, 2nd edn. Elsevier, Philadelphia, pp 223–238

  132. Skodda S (2012) Effect of deep brain stimulation on speech performance in Parkinson’s disease. Parkinsons Dis. doi:10.1155/2012/850596

    PubMed  PubMed Central  Google Scholar 

  133. Skodda S, Rinsche H, Schlegel U (2009) Progression of dysprosody in Parkinson’s disease over time—a longitudinal study. Mov Disord 24:716–722

    PubMed  Article  Google Scholar 

  134. Skodda S, Visser W, Schlegel U (2010) Short- and long-term dopaminergic effects on dysarthria in early Parkinson’s disease. J Neural Transm 117:197–205. doi:10.1007/s00702-009-0351-5

    CAS  PubMed  Article  Google Scholar 

  135. Skodda S, Flasskamp A, Schlegel U (2011a) Instability of syllable repetition as a marker of disease progression in Parkinson’s disease: a longitudinal study. Mov Disord 26(1):59–64

    PubMed  Article  Google Scholar 

  136. Skodda S, Flasskamp A, Schlegel U (2011b) Instability of syllable repetition in Parkinson’s disease—influence of levodopa and deep brain stimulation. Mov Disord 26(4):728–730

    PubMed  Article  Google Scholar 

  137. Skodda S, Gronheit W, Schlegel U (2011c) Intonation and speech rate in Parkinson’s disease: general and dynamic aspects and responsiveness to levodopa admission. J Voice. doi:10.1016/j.jvoice.2010.04.007

    Google Scholar 

  138. Skodda S, Visser W, Schlegel U (2011d) Gender-related patterns of dysprosody in Parkinson’s disease and correlation between speech variables and motor symptoms. J Voice 25:76–82

    PubMed  Article  Google Scholar 

  139. Skodda S, Visser W, Schlegel U (2011e) Vowel articulation in Parkinson’s disease. J Voice 25:467–472

    PubMed  Article  Google Scholar 

  140. Skodda S, Gronheit W, Schlegel U (2012) Impairment of vowel articulation as a possible marker of disease progression in Parkinson’s disease. PLoS One 7(2):e32132

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  141. Skodda S, Gronheit W, Mancinelli N, Schlegel U (2013) Progression of voice and speech impairment in the course of Parkinson’s disease: a longitudinal study. Parkinson’s Dis 2013:389195

    CAS  Google Scholar 

  142. Skodda S, Gronheit W, Schlegel U, Sudmeyer M, Schnitzler A, Wojtecki L (2014) Effect of subthalamic stimulation on voice and speech in Parkinson’s disease: for the better or worse? Front Neurol 4:218

    PubMed  PubMed Central  Article  Google Scholar 

  143. Smekal Z, Mekyska J, Galaz Z, Mzourek Z, Rektorova I, Faundez-Zanuy M (2015) Analysis of phonation in patients with Parkinson’s disease using empirical mode decomposition. In: 2015 International Symposium on Signals, Circuits and Systems (ISSCS), Iasi, pp 1–4

  144. Spadoto AA, Guido RC, Papa JP, Falcão AX (2010) Parkinson’s disease identification through optimum-path forest. In: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Buenos Aires, pp 6087–6090

  145. Spencer KA, Rogers MA (2005) Speech motor programming in hypokinetic and ataxic dysarthria. Brain Lang 94:347–366

    PubMed  Article  Google Scholar 

  146. Tanaka Y, Tsuboi T, Watanabe H et al (2015) Voice features of Parkinson’s disease patients with subthalamic nucleus deep brain stimulation. J Neurol 262:1173–1181. doi:10.1007/s00415-015-7681-z

    PubMed  Article  Google Scholar 

  147. Tripoliti E, Zrinzo L, Martinez-Torres I et al (2011) Effects of subthalamic stimulation on speech of consecutive patients with Parkinson disease. Neurology 76:80–86. doi:10.1212/WNL.0b013e318203e7d0

    CAS  PubMed  Article  Google Scholar 

  148. Tripoliti E, Limousin P, Foltynie T et al (2014) Predictive factors of speech intelligibility following subthalamic nucleus stimulation in consecutive patients with Parkinson’s disease. Mov Disord 29:532–538. doi:10.1002/mds.25816

    CAS  PubMed  Article  Google Scholar 

  149. Tsanas A, Little MA, McSharry PE, Ramig LO (2010a) Accurate telemonitoring of Parkinson’s disease progression by noninvasive speech tests. IEEE Trans Biomed Eng 57:884–893

    PubMed  Article  Google Scholar 

  150. Tsanas A, Little MA, McSharry PE, Ramig LO (2010b) New nonlinear markers and insights into speech signal degradation for effective tracking of Parkinson’s disease symptom severity. In: International Symposium on Nonlinear Theory and its Applications (NOLTA 2010): pp 457–460

  151. Tsanas A, Little MA, McSharry PE, Ramig LO (2010b) Nonlinear speech analysis algorithms mapped to a standard metric achieve clinically useful quantification of average Parkinson’s disease symptom severity. J R Soc Interface 8:842–855

    PubMed  PubMed Central  Article  Google Scholar 

  152. Tsanas A, Little MA, McSharry PE, Spielman J, Ramig LO (2012) Novel speech signal processing algorithms for high-accuracy classification of Parkinson’s disease. IEEE T Biomed Eng 59(5):1264–1271

    Article  Google Scholar 

  153. Tsuboi T, Watanabe H, Tanaka Y et al (2014) Distinct phenotypes of speech and voice disorders in Parkinson’s disease after subthalamic nucleus deep brain stimulation. J Neurol Neurosurg Psychiatry 0:1–9. doi:10.1136/jnnp-2014-308043

    Google Scholar 

  154. Tsuboi T, Watanabe H, Tanaka Y et al (2015) Characteristic laryngoscopic findings in Parkinsons disease patients after subthalamic nucleus deep brain stimulation and its correlation with voice disorder. J Neural Transm 122:1663–1672. doi:10.1007/s00702-015-1436-y

    CAS  PubMed  Article  Google Scholar 

  155. Tykalova T, Rusz J, Cmejla R et al (2015) Effect of dopaminergic medication on speech dysfluency in Parkinson’s disease: a longitudinal study. J Neural Transm 122:1135–1142. doi:10.1007/s00702-015-1363-y

    PubMed  Article  Google Scholar 

  156. Vanhoutte S, De Letter M, Corthals P, Van Borsel J, Santens P (2012) Quantitative analysis of language production in parkinson’s disease using a cued sentence generation task. Clin Linguist Phon 26:863–881

    PubMed  Article  Google Scholar 

  157. Vásquez-Correa JC, Arias-Vergara T, Orozco-Arroyave JR, Vargas-Bonilla JF, Arias-Londoño JD, Nöth E (2015) Automatic detection of Parkinson’s disease from continuous speech recorded in non-controlled noise conditions. In: Proceedings of 16th INTERSPEECH, Dresden, Germany, pp 105–109

  158. Vaziri G, Almasganj F, Behroozmand R (2010) Pathological assessment of patients speech signals using nonlinear dynamical analysis. Comput Biol Med 40(1):54–63

    PubMed  Article  Google Scholar 

  159. Villa-Canas T, Orozco-Arroyave JR, Vargas-Bonilla JF, Arias-Londoño JD (2014) Modulation spectra for automatic detection of Parkinson’s disease. In: 2014 XIX Symposium on Image, Signal Processing and Artificial Vision (STSIVA), Armenia, pp 1–5

  160. Wang EQ, Metman LV, Bakay RAE et al (2006) Hemisphere-specific effects of subthalamic nucleus deep brain stimulation on speaking rate and articulatory accuracy of syllable repetitions in Parkinson’s disease. J Med Speech Lang Pathol 14:323–334

    PubMed  PubMed Central  Google Scholar 

  161. Xie Y, Zhang Y, Zheng Z et al (2011) Changes in speech characters of patients with Parkinson’s disease after bilateral subthalamic nucleus stimulation. J Voice 25:751–758. doi:10.1016/j.jvoice.2010.08.002

    PubMed  Article  Google Scholar 

  162. Yorkston K, Beukelman D (1984) Assessment of Intelligibility of dysarthric speech. Pro-ed, Austin

    Google Scholar 

Download references

Acknowledgements

This work was supported by the grant of the Czech Ministry of Health NV16-30805A (Effects of non-invasive brain stimulation on hypokinetic dysarthria, micrographia, and brain plasticity in patients with Parkinson’s disease).

Author information

Affiliations

Authors

Corresponding author

Correspondence to Irena Rektorova.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Brabenec, L., Mekyska, J., Galaz, Z. et al. Speech disorders in Parkinson’s disease: early diagnostics and effects of medication and brain stimulation. J Neural Transm 124, 303–334 (2017). https://doi.org/10.1007/s00702-017-1676-0

Download citation

Keywords

  • Hypokinetic dysarthria
  • Parkinson’s disease
  • Acoustic analysis
  • rTMS
  • DBS
  • Dopaminergic medication
  • Functional imaging