AUTOMATIC-ANALYSIS OF AUDIOGRAMS IN EPIDEMIOLOGIC SURVEILLANCE

被引：0
|
作者：
JOB, A
DELPLACE, F
ARVERS, P
GORZERINO, P
GRATEAU, P
PICARD, J
机构：
来源：
REVUE D EPIDEMIOLOGIE ET DE SANTE PUBLIQUE | 1993年 / 41卷 / 05期
关键词：
AUDIOMETRY; IMPULSE NOISE; PRINCIPAL COMPONENT ANALYSIS; HEARING LOSS; EPIDEMIOLOGIC SURVEILLANCE;
D O I：
暂无
中图分类号：
R1 [预防医学、卫生学];
学科分类号：
1004 ; 120402 ;
摘要：
We have developed a method for the assessment of auditive loss using a sample of 1794 Bekesy audiograms recorded in young military students. A rectangular digital filter was used to smooth rough audiogram signals so as to detect pathological patterns such as scotoms and recruitments. Three factors were extracted from principal component analysis. They were correlated with the usual auditory indices and explained 70% of the total observed variance. The first factor is a general indicator of deafness, while the second and third describe the shapes of the hearing threshold level (asymmetry and convexity). This method can be used for rapid identification of suspect audiograms and is thus of value for epidemiological surveillance of populations exposed to impulsive noise.
引用
收藏
页码：407 / 415
页数：9
相关论文
共 50 条
  • [41] Automatic selection of a representative trial from multiple measurements using Principle Component Analysis
    Katrin, Schweizer
    Philippe, Cattin C.
    Reinald, Brunner
    Bert, Mueller
    Cora, Huber
    Jacqueline, Romkes
    JOURNAL OF BIOMECHANICS, 2012, 45 (13) : 2306 - 2309
  • [42] Automatic detection of skin defects in citrus fruits using a multivariate image analysis approach
    Lopez-Garcia, Fernando
    Andreu-Garcia, Gabriela
    Blasco, Jose
    Aleixos, Nuria
    Valiente, Jose-Miguel
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2010, 71 (02) : 189 - 197
  • [43] Identification of Unexpected Behavior of an Automatic Teller Machine Using Principal Component Analysis Models
    Simutis, Rimvydas
    Dilijonas, Darius
    Bastina, Lidija
    BUSINESS INFORMATION SYSTEMS WORKSHOPS, 2009, 37 : 53 - +
  • [44] Automatic classification of the interferential tear film lipid layer using colour texture analysis
    Remeseiro, B.
    Penas, M.
    Barreira, N.
    Mosquera, A.
    Novo, J.
    Garcia-Resua, C.
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2013, 111 (01) : 93 - 103
  • [45] Use of principal component analysis for automatic classification of epileptic EEG activities in wavelet framework
    Acharya, U. Rajendra
    Sree, S. Vinitha
    Alvin, Ang Peng Chuan
    Suri, Jasjit S.
    EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (10) : 9072 - 9078
  • [46] SEMPCA-SUMMARIZER: EXPLOITING SEMANTIC PRINCIPAL COMPONENT ANALYSIS FOR AUTOMATIC SUMMARY GENERATION
    Alcon, Oscar
    Lloret, Elena
    COMPUTING AND INFORMATICS, 2018, 37 (05) : 1126 - 1148
  • [47] Automatic epilepsy detection using wavelet-based nonlinear analysis and optimized SVM
    Li, Mingyang
    Chen, Wanzhong
    Zhang, Tao
    BIOCYBERNETICS AND BIOMEDICAL ENGINEERING, 2016, 36 (04) : 708 - 718
  • [48] Analysis of risk factors and targeted surveillance for postnatal hearing loss during 25 years of hearing screening
    Ignacio Benito-Orejas, Jose
    Eduardo Ramirez-Salas, Jesus
    Viveros-Diez, Patricia
    Duque-Holguer, Victoria
    Ramirez-Cano, Beatriz
    Morais-Perez, Dario
    REVISTA ORL, 2021, 12 (03) : 197 - 216
  • [49] Automatic Test Case Generation Using Many-Objective Search and Principal Component Analysis
    Li, Dongcheng
    Wong, W. Eric
    Pan, Sean
    Koh, Liang-Seng
    Li, Shenglong
    Chau, Matthew
    IEEE ACCESS, 2022, 10 : 85518 - 85529
  • [50] PREDICTION OF FINANCIAL DISTRESS BY MULTIVARIATE STATISTICAL ANALYSIS: THE CASE OF FIRMS TAKEN INTO THE SURVEILLANCE MARKET IN THE ISTANBUL STOCK EXCHANGE
    Canbas, Serpil
    Onal, Yildirim B.
    Duzakin, Hatice G.
    Kilic, Suleyman B.
    INTERNATIONAL JOURNAL OF THEORETICAL AND APPLIED FINANCE, 2006, 9 (01) : 133 - 150
12345