A Software System for Diagnosis and Classification of Deafness

Transcription

1 European Journal of Scientific Research ISSN X Vol.25 No.4 (2009), pp EuroJournals Publishing, Inc A Software System for Diagnosis and Classification of Deafness Dunmade A.O Information Technology Office, Faculty of Science University of Ilorin, Ilorin, Nigeria Dunmade A.D Dept. of Otorhinolaryngology, College of Medicine University of Ilorin, Ilorin, Nigeria Taiwo O.A Dept. of Mathematics, University of Ilorin, Ilorin, Nigeria Tomori A.R Computer Services and Information Technology (COMSIT) Directorate University of Ilorin, Ilorin, Nigeria Komolafe T.M Dept. of Statistics, University of Ibadan, Ibadan, Nigeria Abstract This work attempts to model the expert reasoning processes of an Ear, Nose and Throat surgeon (otorhinolaryngologist) in his everyday work of diagnosing the level of deafness in his patients, via the use of the Pure Tone Audiometry (PTA) test. The coding is done using the Visual Prolog language. Data obtained from five patients is used to test the software Keywords: Artificial Intelligence, Expert Systems, Deafness. Introduction Deafness is a disease that cuts across a broad spectrum of our society. No social class or strata can claim to be free from its clutches. It strikes at both the rich and poor with reckless abandon. It is the state in which one is unable to hear well or unable to hear at all. The term unable to hear well can be equally called hearing loss or hearing deficiency. Deafness in our environment is almost synonymous to a life of silence and isolation (Holborow et al, 1982), (0Ijaduola, 1982). In most developing countries in Africa, Nigeria inclusive, the causes are unknown; probably congenital. In about one-third of studies, the main acquired causes were febrile illnesses, meningitis, mumps, rubella and severe birth asphyxia. Other acquired causes include ototoxicity, neonatal jaundice and birth trauma (Dunmade et al, 2006). In making diagnosis of deafness apart from a detailed patient history that has to be taken and physical examination, a simple audiological investigation via the use of the Pure Tone Audiometry test among other investigations were used to assess hearing impairment. This study aims at modeling the expert reasoning processes of an Ear, Nose and Throat Surgeon in making diagnosis via PTA using the Visual Prolog Software.

2 A Software System for Diagnosis and Classification of Deafness 598 Partial deafness ranging from mild via moderate to severe is most commonly the result of an ear disease, injury or degeneration of the hearing mechanism with age (Smith, 1999). Causes of Deafness Conductive Smith (1999) says that in an adult, the most common cause of conductive deafness is ear wax blocking the outer canal. Less commonly is otosclerosis (loss of normal mobility of the stapes). In children, otitis media (middle ear infection) and glue ear (collection of sticky fluid in the middle ear) are by far the most common causes of this type of deafness. Rarely, conductive deafness can be caused by barotrauma (damage to the ear drum or middle ear due to sudden pressure changes in an air craft or under water or by a perforated ear drum following injury), a middle ear infection or surgery on the ear. Sensorineural Defects of the inner ear are sometimes congenital (from birth), due to an inherited fault in a chromosome or to birth injury or bad development in pregnancy or babyhood jaundice. If it is later in life, this may be due to damage to the ear as a result of loud noise, drugs, or a degeneration of the body parts due to old age (Dunmade et al, 2006). Causes of Deafness Deafness could be either congenital i.e. from birth, or acquired. The Figure 1 below shows various causes based on these two parameters. Figure 1: Causes of Deafness Congenital: 1. maternal rubella 2. hereditary/familial diseases 3. ototoxicity drugs and native concoctions used during pregnancy Acquired: 1. ototoxicity drugs and native concoctions used to treat ailments. 2. severe birth asphyxia 3. cerebral palsy 4. febrile illnesses 5. age 6. infections 7. occupational 8. accidental

3 599 Dunmade A.O, Dunmade A.D, Taiwo O.A, Tomori A.R and Komolafe T.M Methods of Diagnosing Deafness There are various methods of diagnosing deafness, as the figure 2 below shows. Figure 2: METHODS OF DIAGNOSING DEAFNESS Detailed taking of patient history Physical examination Clinical 1. wristwatch ticking 2. conversational sounds 3. loud test Investigations Laboratory 1. pure Tone Audiometry test 2. tympanometry 3. evoke response audiometry Incidence Deafness at birth is sensorineural and incurable, however, it is rare. i.e. 1 in 1000 babies (Brobby, 2006). Deafness in young children may be conductive or sensorineural and may be curable 15. Deafness in older adults may be due to a degeneration of the body and may be cured by the use of a hearing aid. Symptoms Signs and Diagnosis A baby suffering from congenital deafness fails to respond to sounds, and although crying is often normal, he or she does not make the normal baby rudimentary vocalization and verbalization sounds that normally precedes speech. These symptoms may first be noticed by a parent. In a young child, a health visitor or doctor may conduct hearing tests during regular medical checks to detect any hearing loss. In an adult who has started becoming deaf, sounds heard are not only quieter than before, but are also distorted and less clear, high tones are less audible than low ones. Tests are carried out to determine whether deafness is conductive (external ear to middle ear) or sensorineurial. (sensory and neural pathway inner ear hearing mechanisms). Treatment Children born deaf may need special device, a cochlear implants & instruction if they are to speak. The process is long and difficult, but eventually many children learn to communicate effectively with sign language. Operations may also be performed in some cases or syringing (flushing the ear with water) may be done to remove ear wax. Hearing aids may also be used to lessen deafness.

4 A Software System for Diagnosis and Classification of Deafness 600 Definitions Artificial Intelligence Generally, AI techniques consist of making a computer do something that if it were done by a human being would be considered important (Olatunbosun et al, 1999), (Clark and Tarnaud, 1982). Expert Systems A system that handles real world complex problems that require an expert s interpretation (Boullary, 1992). The expert solves these problems using a computer model of Expert Human reasoning, reaching the same conclusion that the human expert would reach if faced with a comparable problem (Futo and Gergely, 1990). Their expertise is composed of skills and analytical knowledge specific to them which are far above the usual standard in a particular domain (Harris, 1998). The expert is able to solve problems in his domain of expertise far better and faster than anyone else. He can detect new problems. A computer based expert System is a production system whose knowledge is captured from one or more experts (Boy, 1991), (Golumbic, 1990). Mathematical Basis for Using Prolog The Runge Kutta Method Prolog makes it possible to define equations and their corresponding initial values. Our interest is to define a software that will help to diagnose and define the state of hearing impairedness (or otherwise) of a particular patient. We therefore solve the model equation numerically, using Runge-Kutta of order 2 (Dunmade, 2004). One of the Computational difficulties associated with linear multi-step formulas is the need for alternative starting procedures. The exceptions to this are the 1-step methods, but unfortunately, they are of low order accuracy. Indeed, the best 1-step method is the trapezoidal method and this is only convergent of order 2. Consider the Euler trapezoidal predictor pair * and **. Suppose that just one correction is applied so that Y [0] n+1=y n +hƒ(x n, y n ) * y n+1 = y [1] n + h [ƒ(x n, y n )+ ƒ(x n, h,y n + hƒ(x n, y n ))] ** 2 Substitution of the expression for Y [0] n+1 into that of y n+1 gives y n+1 = y n + h [ƒ(x n, y n )+ ƒ(x n, h,y n + hƒ(x n, y n ))] 2 Hence, if we define K 1 = ƒ(x n, y n ) K 2 = ƒ(x n, h,y n +hk 1 ) Then, y n+1 = y n + h [K 1 + K 2 ] 2 Written in this form, the method is called a 2-stage Runge-Kutta method. The numerical value of K 1 is substituted to determine K 2. These numbers are then used to calculate y n+1. The general R-stage Runge-Kutta method is defined by K 1 = ƒ(x n, y n ) s-1 s-1 K s = ƒ(x n, hσ b 1,y n + hσ b 1,k 1 ) s=2,3 R t=1 i=1

5 601 Dunmade A.O, Dunmade A.D, Taiwo O.A, Tomori A.R and Komolafe T.M R y n+1 = y n + hσ c s,k s s=1 for appropriate constants b 1 c s The most popular method of this type is the classical 4-stage method K 1 = ƒ(x n, y n ) K 2 = ƒ(x n, + ½h,y n + ½hk 1 ) K 3 = ƒ(x n, + ½h,y n + ½hk 2 ) K 4 = ƒ(x n, + h,y n + hk 3 ) y n+1 = y n + h [K 1 + 2K 2 + 2K 3 + k 4 ] 6 [m+1] [m] Y n+1 = y n + h [ƒ(x n, y n )+ ƒ( xn+1, y n+1 )] 2 A starting value Y [0] n+1 has to be supplied. This can be calculated from Euler s formula as Y [0] n+1 = y n + hƒ(x n, y n ) (Abdulwahab and Guenther, 2002). The Software In the process of developing a software, the scientists and engineers study various areas and techniques of designing software with a view to efficiently and effectively sorting and retrieving information. Many factors must be put into consideration when writing a software 14. For instance, since computers have only a limited amount of memory, the designers must limit the number of features included in the program so as not to exceed the requirements of the system it is designed for 15. This software was written using Visual Prolog. For this work, the PTA Test is used as a means of identifying and classifying the severity and type of deafness in a patient, and suggesting a likely solution to the problem. However, the source code for this software was not included as a part of this article because it is too lengthy. (over 1,300 lines of source code.) Evaluation The Pure Tone Audiometry (PTA) test is the diagnostic method under study in the course of this work. Its functionalities are as follows: 1. Subjectivity i.e. it relies on patient response. 2. Different graduated tones measured in Hertz (125Hz to 8kHz) are applied to the patient in a sound proofed environment at different frequencies. Patient relays response by pressing a button at each heard frequency. 3. It s main disadvantage is that it allows for malingering i.e. the patient is able to manipulate or distort the response.

6 A Software System for Diagnosis and Classification of Deafness 602 Treatment and Diagnosis of Categories of Deafness Table 1: Category (PTA) Mild Moderate Probable Diagnosis & Treatment 1. Remove the cause e.g. wax, foreign body 2. Treat the cause via drugs. E.g. use of antibiotics, systemic decongestants, etc 3. Use of grommets e.g. middle ear effusion (otitis media) 1. Remove the cause e.g. impacted wax. 2. Treat the cause via drugs, e.g. chronic otitis media. 3. Surgical correction e.g. tympanometry and ossiculoplasty Severe 1. Remove the cause if no solution place the patient on hearing aid as in presbyacusis age induced hearing loss. Profound 1. Place on powerful hearing aid to convert to moderate (if possible). 2. put on cochlear implant to stimulate nerve endings. Different areas have different noise range levels depending on environmental factors. Heavily industrialized areas have higher range levels as a result of machinery, traffic and human noise more than the rural areas. For this study, normal hearing range is taken as 0 19 decibels (db) A decibel is a unit of measurement of the intensity of noise. Frequencies Table 2: Table 3: in db Response 0 19 normal hearing mild hearing loss moderate hearing loss severe hearing loss profound hearing loss Below is a table showing the data used by each of the test cases and the diagnosis given by the Software Test case No PTA Test Range Software Diagnosis to 80 (moderate to severe) Middle frequency sensorineural hearing loss genetic recessive disorder e.g. birth defect to 60 (mild to moderate) Sensorineural hearing loss with notch at 6kHz (noise induced hearing loss occupational) to 90 (mild to severe) Sensorineural hearing loss. High frequency sloping (presbyacusis old age induced) to 40 (mild) Conductive loss maximum at low frequency- patient with otitis media to 70 (moderate to severe) Conductive hearing loss with Carhart notch at 2kHz. Patient with Otosclerosis loss of mobility of stapes (bone in the middle ear) It is necessary to note that all patient data such as Patient Name, Age, Sex, Hospital Number, Date, Name of Audiologist, Audiometer,Test Consistency, Occupation and all other relevant data will be filled in on the physical paper form, and also captured electronically. Both ears may be tested, depending on the nature of the complaint of the patient. Below are the scanned copies of the physical (paper) results of the PTA test performed on the test cases numbered 1 to 5and the output generated by the software.

7 603 Dunmade A.O, Dunmade A.D, Taiwo O.A, Tomori A.R and Komolafe T.M Test Case 1: Middle frequency sensorineural hearing loss genetic recessive disorder e.g. birth defect Test Case 2: Sensorineural hearing loss with notch at 6kHz (noise induced hearing loss occupational) Test Case 3: Sensorineural hearing loss. High frequency sloping (presbyacusis old age induced)

8 A Software System for Diagnosis and Classification of Deafness 604 Test Case 4: Conductive loss maximum at low frequency suggestive of a patient with otitis media. Test Case 5: Conductive hearing loss with Carhart notch at 2kHz. Patient with Otosclerosis loss of mobility of stapes (bone in the middle ear) Conclusion Using the model equations, a numerical scheme was used to develop a software capable of diagnosing deafness. It is important to note that this software helps the medical practitioner- the otorhinolaryngologist in his task of determining the severity of deafness in each individual patient case. The conclusion of this work therefore is that this software is an important tool for the ENT Doctor and audiologist as it helps them to understand clearly the level of severity of deafness of each patient that comes his way.

9 605 Dunmade A.O, Dunmade A.D, Taiwo O.A, Tomori A.R and Komolafe T.M References [1] Abdelwahab K. and Guenther R. B. (2002) An Introduction to numerical Analysis Methods: A MATLAB Approach, Chapman and Hall, CRC. [2] Ayeni O., Adewale S. O., (2008). Software System for Diagnosis & Classification of Diabetes Mellitus. Conference Proceedings of Nigeria Computer Society held between 24 27th June. [3] Boy G. (1991) Intelligent Assistant Systems. Academic Press. [4] Brobby G.W. (1988) Causes of Congenital and Acquired Totasl Sensorineural Hearing Loss in Ghanaian Children. Tropical Doctor 18, [5] Chukwuezi A. B. (1991) Profound and Total Deafness in Owerri, Nigeria. East African Medical Journal 68, [6] Clark K.L. and Tarnaud S.A. (1982) Logic Programming academy Press, London, U.K. [7] Dunmade A. D., Segun-Busari S, Olajide TG, Ologe FE (2006). Profound Bilateral Sensorineural Hearing Loss in Nigerian Children. Any Shift in Etiology? Journal of Deaf Studies and Deaf Education 12, [8] Dunmade A. O. (2004). M.Sc Thesis submitted to the Department of Computer Science, University of Ilorin, Ilorin, Nigeria. [9] Futo, I. and Gergely, T. (1990) Artificial Intelligence simulation. Ellis Limited. [10] Golumbic M.C. (Ed.) Advances in Artificial Intelligence. Springer Cerlag New York inc. [11] Harris C.J. (1988). Application of Artificial Intelligence to Command and Control systems. Peter Peregrinus Publishers. [12] Holborow C, Martinson F. D. and Auger N (1982). A study of Deafness in West Africa. International Journal of Paediatric Otorhinolaryngology4: [13] Ijaduola G. T. A. (1982) the Problems of the Profoundly Deaf Nigerian Child. Post Graduate Doctor- Africa 4: [14] Olatunbosun A.O., Afolabi T.M. and Uwaifo N.O. (1997) An Advisory Expert system for Research into the Molecular and Morphological Basis of Cancer. B. Sc Thesis submitted to the Department of Computer Science, University of Ibadan, Ibadan, Nigeria. [15] Oyewole O. A. (2007). An Object Oriented Software for Accessing Staff Records in a Tertiary Institution: B. Tech Thesis, LAUTECH, Ogbomosho, Nigeria. [16] Smith T. (Ed.) (1999), British Medical Association A to Z. Family Health Encyclopedia, Dorling Kindersley Publishers.