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  1. Chan MY, Chu SY, Ahmad K, Ibrahim NM
    J Telemed Telecare, 2021 Apr;27(3):174-182.
    PMID: 31431134 DOI: 10.1177/1357633X19870913
    INTRODUCTION: Intensive voice therapy is one of the best evidence-based treatments to improve speech and voice difficulties to individuals with Parkinson's disease (PD). However, accessibility to intensive voice therapy is highly challenging in Malaysia due to the lack of voice specialised speech-language therapists. This study examined the feasibility of using smartphone videoconference to deliver intensive voice therapy to individuals with PD in Malaysia.

    METHODS: Intensive voice therapy was delivered to 11 adults with PD using a smartphone videoconference method via WhatsApp Messenger freeware. The therapy consisted of 12 sessions over four weeks and focused on increasing vocal loudness. Outcomes were assessed using objective, perceptual and quality-of-life measures pre and post treatment. Participant satisfaction with the telerehabilitation method was obtained via the Smartphone-Based Therapy Satisfaction Questionnaire.

    RESULTS: Significant gains were reported for sound pressure level in sustained vowels and monologue. Perceptual ratings showed significant improvements in overall mean severity and loudness after treatment. Mean scores of speech intelligibility and Voice Handicap Index-10 were significantly better post treatment. Overall, participants were highly satisfied with the smartphone videoconference method.

    DISCUSSION: Present results suggest that the smartphone videoconference method is feasible to deliver intensive voice therapy to individuals with PD to gain better speech and voice functions. Future studies need to address the standardisation of the system protocol to optimise this novel service delivery method in Malaysia.

    Matched MeSH terms: Voice Disorders*
  2. Ali Z, Elamvazuthi I, Alsulaiman M, Muhammad G
    J Med Syst, 2016 Jan;40(1):20.
    PMID: 26531753 DOI: 10.1007/s10916-015-0392-2
    Voice disorders are associated with irregular vibrations of vocal folds. Based on the source filter theory of speech production, these irregular vibrations can be detected in a non-invasive way by analyzing the speech signal. In this paper we present a multiband approach for the detection of voice disorders given that the voice source generally interacts with the vocal tract in a non-linear way. In normal phonation, and assuming sustained phonation of a vowel, the lower frequencies of speech are heavily source dependent due to the low frequency glottal formant, while the higher frequencies are less dependent on the source signal. During abnormal phonation, this is still a valid, but turbulent noise of source, because of the irregular vibration, affects also higher frequencies. Motivated by such a model, we suggest a multiband approach based on a three-level discrete wavelet transformation (DWT) and in each band the fractal dimension (FD) of the estimated power spectrum is estimated. The experiments suggest that frequency band 1-1562 Hz, lower frequencies after level 3, exhibits a significant difference in the spectrum of a normal and pathological subject. With this band, a detection rate of 91.28 % is obtained with one feature, and the obtained result is higher than all other frequency bands. Moreover, an accuracy of 92.45 % and an area under receiver operating characteristic curve (AUC) of 95.06 % is acquired when the FD of all levels is fused. Likewise, when the FD of all levels is combined with 22 Multi-Dimensional Voice Program (MDVP) parameters, an improvement of 2.26 % in accuracy and 1.45 % in AUC is observed.
    Matched MeSH terms: Voice Disorders/diagnosis*; Voice Disorders/physiopathology*
  3. RoscellaInja, Abdul Rahman H
    MyJurnal
    Teachers face one of the highest demands of any professional group to use their voices at work. Thus, they are at
    higher risk of developing voice disorder than the general population. The consequences of voice disorder may have
    impact on teacher’s social and professional life as well as their mental, physical and emotional state and their
    ability to communicate. Objectives of this study are to determine the prevalence of voice disorder and the
    relationship between voice disorder with associated risk factors such as teaching activities and lifestyle factors
    among primary school teachers in Bintulu, Sarawak. A cross sectional study was conducted based on random sample
    of 4 primary schools in Bintulu, Sarawak between January-March 2014. A total of 100 full-time primary school
    teachers were invited to participate in the study. Data were collected through a self-administered questionnaire
    addressing the prevalence of voice disorder and potential risk factors. Descriptive analysis and chi-square test was
    used to measure the relationship between voice disorder and associated risk factors. The response rate for this study
    was 78% (78/100). The study found that the prevalence of voice disorder among primary school teachers in Bintulu,
    Sarawak was 13%. Chi-square test results revealed that factors significantly associated with voice disorder (p
    Matched MeSH terms: Voice Disorders*
  4. Mat Baki M, Wood G, Alston M, Ratcliffe P, Sandhu G, Rubin JS, et al.
    Clin Otolaryngol, 2015 Feb;40(1):22-8.
    PMID: 25263076 DOI: 10.1111/coa.12313
    OBJECTIVE: To evaluate the agreement between OperaVOX and MDVP.

    DESIGN: Cross sectional reliability study.

    SETTING: University teaching hospital.

    METHODS: Fifty healthy volunteers and 50 voice disorder patients had supervised recordings in a quiet room using OperaVOX by the iPod's internal microphone with sampling rate of 45 kHz. A five-seconds recording of vowel/a/was used to measure fundamental frequency (F0), jitter, shimmer and noise-to-harmonic ratio (NHR). All healthy volunteers and 21 patients had a second recording. The recorded voices were also analysed using the MDVP. The inter- and intrasoftware reliability was analysed using intraclass correlation (ICC) test and Bland-Altman (BA) method. Mann-Whitney test was used to compare the acoustic parameters between healthy volunteers and patients.

    RESULTS: Nine of 50 patients had severe aperiodic voice. The ICC was high with a confidence interval of >0.75 for the inter- and intrasoftware reliability except for the NHR. For the intersoftware BA analysis, excluding the severe aperiodic voice data sets, the bias (95% LOA) of F0, jitter, shimmer and NHR was 0.81 (11.32, -9.71); -0.13 (1.26, -1.52); -0.52 (1.68, -2.72); and 0.08 (0.27, -0.10). For the intrasoftware reliability, it was -1.48 (18.43, -21.39); 0.05 (1.31, -1.21); -0.01 (2.87, -2.89); and 0.005 (0.20, -0.18), respectively. Normative data from the healthy volunteers were obtained. There was a significant difference in all acoustic parameters between volunteers and patients measured by the Opera-VOX (P 

    Matched MeSH terms: Voice Disorders/diagnosis*; Voice Disorders/physiopathology*
  5. Ali Z, Alsulaiman M, Muhammad G, Elamvazuthi I, Al-Nasheri A, Mesallam TA, et al.
    J Voice, 2017 May;31(3):386.e1-386.e8.
    PMID: 27745756 DOI: 10.1016/j.jvoice.2016.09.009
    A large population around the world has voice complications. Various approaches for subjective and objective evaluations have been suggested in the literature. The subjective approach strongly depends on the experience and area of expertise of a clinician, and human error cannot be neglected. On the other hand, the objective or automatic approach is noninvasive. Automatic developed systems can provide complementary information that may be helpful for a clinician in the early screening of a voice disorder. At the same time, automatic systems can be deployed in remote areas where a general practitioner can use them and may refer the patient to a specialist to avoid complications that may be life threatening. Many automatic systems for disorder detection have been developed by applying different types of conventional speech features such as the linear prediction coefficients, linear prediction cepstral coefficients, and Mel-frequency cepstral coefficients (MFCCs). This study aims to ascertain whether conventional speech features detect voice pathology reliably, and whether they can be correlated with voice quality. To investigate this, an automatic detection system based on MFCC was developed, and three different voice disorder databases were used in this study. The experimental results suggest that the accuracy of the MFCC-based system varies from database to database. The detection rate for the intra-database ranges from 72% to 95%, and that for the inter-database is from 47% to 82%. The results conclude that conventional speech features are not correlated with voice, and hence are not reliable in pathology detection.
    Matched MeSH terms: Voice Disorders/diagnosis*; Voice Disorders/physiopathology
  6. Moy FM, Hoe VC, Hairi NN, Chu AH, Bulgiba A, Koh D
    PLoS One, 2015;10(11):e0141963.
    PMID: 26540291 DOI: 10.1371/journal.pone.0141963
    OBJECTIVES: To establish the prevalence of voice disorder using the Malay-Voice Handicap Index 10 (Malay-VHI-10) and to study the determinants, quality of life, depression, anxiety and stress associated with voice disorder among secondary school teachers in Peninsular Malaysia.

    METHODS: This study was divided into two phases. Phase I tested the reliability of the Malay-VHI-10 while Phase II was a cross-sectional study with two-stage sampling. In Phase II, a self-administered questionnaire was used to collect socio-demographic and teaching characteristics, depression, anxiety and stress scale (Malay version of DASS-21); and health-related quality of life (Malay version of SF12-v2). Complex sample analysis was conducted using multivariate Poisson regression with robust variance.

    RESULTS: In Phase I, the Spearman correlation coefficient and Cronbach alpha for total VHI-10 score was 0.72 (p < 0.001) and 0.77 respectively; showing good correlation and internal consistency. The ICCs ranged from 0.65 to 0.78 showing fair to good reliability and demonstrating the subscales to be reliable and stable. A total of 6039 teachers participated in Phase II. They were primarily Malays, females, married, had completed tertiary education and aged between 30 to 50 years. A total of 10.4% (95% CI 7.1, 14.9) of the teachers had voice disorder (VHI-10 score > 11). Compared to Malays, a greater proportion of ethnic Chinese teachers reported voice disorder while ethnic Indian teachers were less likely to report this problem. There was a higher prevalence ratio (PR) of voice disorder among single or divorced/widowed teachers. Teachers with voice disorder were more likely to report higher rates of absenteeism (PR: 1.70, 95% CI 1.33, 2.19), lower quality of life with lower SF12-v2 physical (0.98, 95% CI 0.96, 0.99) and mental (0.97, 95% CI 0.96, 0.98) component summary scales; and higher anxiety levels (1.04, 95% CI 1.02, 1.06).

    CONCLUSIONS: The Malay-VHI-10 is valid and reliable. Voice disorder was associated with increased absenteeism, marginally associated with reduced health-related quality of life as well as increased anxiety among teachers.

    Matched MeSH terms: Voice Disorders/etiology*; Voice Disorders/epidemiology*
  7. Ali Z, Elamvazuthi I, Alsulaiman M, Muhammad G
    J Voice, 2016 Nov;30(6):757.e7-757.e19.
    PMID: 26522263 DOI: 10.1016/j.jvoice.2015.08.010
    BACKGROUND AND OBJECTIVE: Automatic voice pathology detection using sustained vowels has been widely explored. Because of the stationary nature of the speech waveform, pathology detection with a sustained vowel is a comparatively easier task than that using a running speech. Some disorder detection systems with running speech have also been developed, although most of them are based on a voice activity detection (VAD), that is, itself a challenging task. Pathology detection with running speech needs more investigation, and systems with good accuracy (ACC) are required. Furthermore, pathology classification systems with running speech have not received any attention from the research community. In this article, automatic pathology detection and classification systems are developed using text-dependent running speech without adding a VAD module.

    METHOD: A set of three psychophysics conditions of hearing (critical band spectral estimation, equal loudness hearing curve, and the intensity loudness power law of hearing) is used to estimate the auditory spectrum. The auditory spectrum and all-pole models of the auditory spectrums are computed and analyzed and used in a Gaussian mixture model for an automatic decision.

    RESULTS: In the experiments using the Massachusetts Eye & Ear Infirmary database, an ACC of 99.56% is obtained for pathology detection, and an ACC of 93.33% is obtained for the pathology classification system. The results of the proposed systems outperform the existing running-speech-based systems.

    DISCUSSION: The developed system can effectively be used in voice pathology detection and classification systems, and the proposed features can visually differentiate between normal and pathological samples.

    Matched MeSH terms: Voice Disorders/classification; Voice Disorders/diagnosis*; Voice Disorders/physiopathology
  8. Farah Nazlia Che Kassim, Muthusamy, Hariharan, Vijean, Vikneswaran, Zulkapli Abdullah, Rokiah Abdullah
    MyJurnal
    Voice pathology analysis has been one of the useful tools in the diagnosis of the pathological voice, as the method is non-invasive, inexpensive, and can reduce the time required for the analysis. This paper investigates feature extraction based on the Dual-Tree Complex Wavelet Packet Transform (DT-CWPT) using energy and entropy measures tested with two classifiers, k-Nearest Neighbors (k-NN) and Support Vector Machine (SVM). Massachusetts Eye and Ear Infirmary (MEEI) voice disorders database and Saarbruecken Voice Database (SVD) were used. Five datasets of voice samples were used from these databases, including normal and abnormal samples, Cysts, Vocal Nodules, Polyp, and Paralysis vocal fold. To the best of the authors’ knowledge, very few studies were done on multiclass classifications using specific pathology database. File-based and frame-based investigation for two-class and multiclass were considered. In the two-class analysis using the DT-CWPT with entropies, the classification accuracy of 100% and 99.94% was achieved for MEEI and SVD database respectively. Meanwhile, the classification accuracy for multiclass analysis comprised of 99.48% for the MEEI database and 99.65% for SVD database. The experimental results using the proposed features provided promising accuracy to detect the presence of diseases in vocal fold.
    Matched MeSH terms: Voice Disorders
  9. Rahmat O, Prepageran N
    Ear Nose Throat J, 2011 Nov;90(11):E26-7.
    PMID: 22109930
    Matched MeSH terms: Voice Disorders/etiology
  10. Lee ST, Niimi S
    J Laryngol Otol, 1990 Nov;104(11):876-8.
    PMID: 2266311
    Vocal fold sulcus is a cause of dysphonia which has not been recognized until recently. Awareness of its existence combined with use of laryngostroboscopy would enhance the management of this group of patients. Five such cases were treated initially by voice therapy and subsequently combined with microlaryngeal Teflon injections of the vocal cord. Representative photomicrographs and the end results of treatment are presented. A good voice, subjectively and objectively, was obtained in three patients, with satisfactory improvement in the other two.
    Matched MeSH terms: Voice Disorders/therapy
  11. Tai KL, Ng YG, Lim PY
    PLoS One, 2019;14(5):e0217430.
    PMID: 31136594 DOI: 10.1371/journal.pone.0217430
    BACKGROUND: Despite evidence of physical (illness) and mental (stress) health problems, there appears to be a lack of studies or concern regarding occupational safety and health among educators in Malaysia.

    OBJECTIVE: To review the prevalence of illness, stress, and corresponding risk factors among educators in Malaysia.

    METHOD: Scopus, ProQuest, PubMed, ScienceDirect, CAB, and other computerized databases were searched according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to identify studies published between January 2013 and April 2019 on the prevalence and associated risk factors of illness and stress among educators (S1 Checklist). The keywords used included educator, teacher, lecturer, academic staff, teaching profession, university staff, academician, faculty, illness, injury, disease, pain, WMSD, dysphonia, hoarseness, stress, mental health, strain, health problem, disorder, and/or Malaysia. Selected studies were evaluated by quality assessment.

    RESULTS: Twenty-two articles fulfilled the eligibility criteria. The prevalence of illness and stress was determined for low back pain (33.3-72.9%); upper back pain (33.33-56.4%); neck/shoulder pain (40.4-80.1%); upper arm discomfort (91.3%); forearm pain (89.6%); wrist pain (16.7-93.2%); hip pain (13.2-40.9%); thigh discomfort (91.8%); lower leg discomfort (90.5%); knee pain (23.7-88.0%); ankle/feet pain (19.3-87.7%); elbow pain (3.5-13.0%); voice disorder (10.4-13.0%) and stress (5.5-25.9%). Sex, education level, teaching experience, quality of life, anxiety, depression, coping styles, and others were reported as associated risk factors across the studies.

    CONCLUSIONS: There appears to be a cause for concern regarding musculoskeletal disorders, voice disorder, and stress reported among educators in Malaysia. While most risk factors matched those reported in studies elsewhere, others such as school characteristics (school level, government or private school, and location [rural/urban]) have not been investigated.

    Matched MeSH terms: Voice Disorders/epidemiology*
  12. Al-Yahya SN, Muhammad R, Suhaimi SNA, Azman M, Mohamed AS, Baki MM
    J Voice, 2020 Sep;34(5):811.e13-811.e20.
    PMID: 30612893 DOI: 10.1016/j.jvoice.2018.12.003
    OBJECTIVES: Selective laryngeal examination for patients undergoing thyroidectomy is recommended for patients with voice alterations, history of prior cervical or chest surgery, and patients with proven or suspected thyroid malignancy. The study objective is to measure the sensitivity of surgeons in detecting voice abnormalities in patients undergoing thyroidectomy, parathyroidectomy complicated with laryngeal nerve paralysis, or patients with known vocal cords palsy (VCP) due to other neck surgeries.

    DESIGN AND SETTING: Descriptive cross-sectional study in a tertiary center.

    PARTICIPANTS AND METHODS: The subjects are 274 audio files of voices of patients undergoing thyroid, parathyroid surgeries, and known VCP due to other neck surgeries. Voice assessments were done by three endocrine surgeons (A, B, and C) with 20, 12, and 4 years of surgical experience.

    MAIN OUTCOME MEASURES: Sensitivity and specificity of surgeon documented voice assessment in patients with underlying VCP. Subjects' acoustic analysis and Voice Handicap Index (VHI-10) were analyzed.

    RESULTS: Raters A, B, and C have sensitivity of 63.6%, 78.8%, and 66.7%, respectively. Inter-rater reliability shows substantial agreement (ƙ = 0.67). VHI-10 has sensitivity of 75.8% and strong correlation of 0.707 (p value <0.001) to VCP. Subjects with VCP have notably higher jitter, shimmer, and noise-to-harmonic ratio compared to normal subjects with sensitivity of 74.2%, 71.2%, and 72.7%, respectively.

    CONCLUSIONS: The results for surgeons documented voice assessment did not reach the desired sensitivity for a screening tool for patients with underlying VCP. Other tools such as VHI-10 and acoustic analysis may not be used as standalone tools in screening patients with underlying VCP. Routine preoperative laryngeal examination may be recommended for all patients undergoing thyroid, parathyroid, or other surgeries that places the laryngeal nerves at risk.

    Matched MeSH terms: Voice Disorders
  13. Khaled AO, Irfan M, Baharudin A, Shahid H
    Med J Malaysia, 2012 Jun;67(3):289-92.
    PMID: 23082419 MyJurnal
    To describe and determine the possibility of surgical trauma to the external branch of the superior laryngeal nerve and to assess the role of intraoperative neuromonitoring in thyroid surgery.
    Matched MeSH terms: Voice Disorders/etiology*
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