Mean – Variance parametric Model for the Classification based on Cries of Babies

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					                                              (IJCSIS) International Journal of Computer Science and Information Security,
                                                                                                        Vol. 8, No.2, 2010

              Mean – Variance parametric Model for the Classification
                            based on Cries of Babies
           Khalid Nazim S. A.,                                                  Dr. M.B Sanjay Pande
           Research Scholar.                                                    Professor and Head,
                                                                                Department of Computer Science
                                                                                & Engineering, GSSSIETW,
                                                                                Mysore, India.

Abstract- Cry is a feature which makes a individual to                Lieberman stated that it is important to study infant cry
take certain care about the infant which has initiated it. It         as the biological substrate of human speech involves an
is also equally understood that cry makes a person to                 interplay between biological mechanisms that have other
take certain steps. In the present work, we have tried to             vegetative        functions     and     neural     ad     anatomical
implement a mathematical model which can classify the                 mechanisms that appear to have evolved primarily for
cry into its cluster or group based on certain parameters             their role in facilitating human vocal communication
based on which a cry is classified into a normal or                   [12].
abnormal. To corroborate the methodology we taken 17                                Cry has been reported to be used as a diagnostic
distinguished features of cry.                                        tool for the diagnosis of sick babies as other techniques
         The implemented mathematical model takes                     may be invasive and may have varying amounts of risk
into account Doyle’s distance to identify the required                and also require waiting until the infant is of appropriate
features out the 17 features for classifying the dataset.             age. With a recording and analysis of birth cry, the
The dataset of 100 samples were taken to substantiate                 moment of birth itself offers data for an evaluation of the
the efficacy of the Model.                                            infant. Early evaluation leads to possible early detection
    Keywords: Cry, Doyle’s distance.                                  of non normal or high risk infants which has enormous
                                                                      implications in the diagnosis and remediation
                                                                                    The model by Golub assumes that muscle
Is crying a normal activity is a point which opens up                 control is accomplished within three levels of central
many queries based on method or pattern of cry. Cry is a              nervous system processing, i.e., upper, middle and lower
behavior; in fact, it is a sequence of behavior patterns              processors. Each of the three muscle groups important
that is part of the larger behavioral repertoire of the               for     cry     production     is     controlled     independently.
infant. For the neonate and young infant, crying is the               Consequently the parameters that each are responsible
primary mode of expressing and communicating basic                    for are likely to vary independently. Secondly, if one
needs and events. It can be even defined as a signal                  can pinpoint differences in the cry as caused by sub
which can be used to evaluate the neuro-respiratory and               glottal (respiratory), glottal (laryngeal) or supraglottal
phonatory functions of the infants, which leads to the                malfunctions, then one will by able to correlate the
reason that cry pattern is having importance in assessing             acoustic abnormality with specific physiological and
the high risk babies                                                  anatomical abnormalities [13].

                                                                                                    ISSN 1947-5500
                                                       (IJCSIS) International Journal of Computer Science and Information Security,
                                                                                                                 Vol. 8, No.2, 2010

         Crying is the first tool of communication for an            affected sample. This specific problem of classification
infant. These cries seem to be uniform, but there are a lot          can be defined as a Matching Problem. The problem will
of differences between two infants’ cries. A mother can              be a very focused 2-class problem, to be very precise a
distinguish her baby from others according to the crying.            class and a complimentary class problem, where class
An infant cry contains a lot of information about the                refers to a healthy class and a complimentary-class refers
baby,   as   hunger,    pain,   sleepiness   or   boredom            to an unhealthy class [2].
[4,6,7,8].Crying is a behaviour; in fact, it is a sequence
                                                                          II.      METHOD
of behaviour patterns that is part of the larger
                                                                     A. Subjects
behavioural repertoire of the infant. For the neonate and
                                                                     A total of 59 infants were considered for the study which
young infant, crying is the primary mode of expressing
                                                                     comprised 35 normal infants and 24 infants with high
and communicating basic needs and events. For the
                                                                     risk factor. The infants were from neonatal and sick baby
neonate and young infant, crying is the primary mode of
                                                                     wards of JSS hospital, Mysore.
expressing and communicating basic needs and events
                                                                     Group 1: This group comprised of 35 normal infants of
         Cry is a signal which can be used to evaluate
                                                                     the age range less than 24 hrs to 1 month from the
the neuro respiratory and phonatory functions of the
                                                                     neonatal ward of JSS hospital, Mysore. They were born
infants. This is the reason that cry pattern is having so
                                                                     after 37 weeks of gestation and their birth cries were
much of importance in assessing the high risk babies.
                                                                     considered normal. They were born to healthy mothers
The abnormal infant cry is associated with chromosomal,
                                                                     who had normal delivery. The birth weight varied
endocrine, metabolic, and neurological disturbances, as
                                                                     between 2500-3500 gms. These infants were considered
well as malnourishment, toxicity and low birth weight
                                                                     to be completely healthy and normal.
i.e. infants with acoustically abnormal cries are also at
                                                                     Group 2: This group comprised of 24 infants of the age
long-term risk. It is possible to extract certain
                                                                     range less than 24 hours to 1 month form the sick baby
information from the crying sound and use it         to tell
                                                                     ward of JSS hospital, Mysore and with high risk factor
whether the infant is crying due to pain, hunger or some
                                                                     like prematurity, hyper bilirubinemia, jaundice, low birth
other reason. The analysis of the infant cry involves the
                                                                     weight, hypoglycemia, sibling, still birth, consanguinity,
extraction of frequency and amplitude parameters from
                                                                     family history of speech and hearing problems and
cry signal based on the values of these parameters infant
                                                                     multiple risks like delayed birth cry, tachypnoea, birth
is classified as normal or abnormal. Since cry is not one
                                                                     asphyxia, hypertension, hypoplasia of fingers, induced
feature valued, it has many frequency and amplitude
                                                                     labour and hypopiturarism.
parameters. Therefore infant cry constitute the feature
values in a multidimensional space [5].                              B. Data collection
         For the proper assessment of the disease, a                 • Sony digital IC recorder (ICD- P320) which had an in-
knowledge base (KB) of healthy samples with respect to                    built microphone was used for recording the infant
that specific disease would be more useful. This then                     cries
will become useful in developing a model which                       • Laptop (Pentium dual core) with headphone and cable
contrasts a test sample with the KB of healthy samples                    for line feeding of the signal was used for the
and then declares it as a healthy sample if it tallies with               analysis along with PRAAT software (version
the KB satisfactorily; else it decides that the sample is an

                                                                                              ISSN 1947-5500
                                                       (IJCSIS) International Journal of Computer Science and Information Security,
                                                                                                                 Vol. 8, No.2, 2010

       5.0.47; Paul Boersam and David Weenink 2009;                    TABLE I
       University of Amsterdam)
                                                                                         Input                                     Distance
• Sony digital IC recorder (ICD-P320) with microphone                     Element
                                                                                                          Mean       SD
                                                                                                          ( µ1 )     ( σ1 )
       was used to record the infant cries. It was held at a                                                                      of Healthy
                                                                                                                                  Infant cry
       distance of approximately 5cms away from the                                      0.210310694
                                                                    F1: Median pitch                      0.2129     0.1124      0.0466
       mouth of the child. Maximum care was taken to
       control the noise in the room and constant intensity                              0.343033
                                                                    F2: Mean pitch                        0.3284     0.1378      0.0579
       level was maintained for all the recordings. Thus cry
                                                                    F3: Minimum pitch                     0.2398     0.2692      0.1648
       samples of all the 59 infants were recorded.
C. Acoustical Processing                                            F4:Maximum pitch
                                                                                                          0.7231     0.1827      0.0605
           The acoustical analysis is the process through
which the acoustical features are extracted from the                F5: Degree of        0.11075216
                                                                                                          0.2211     0.1661      0.1107
                                                                    voice breaks
crying wave; the process also implies the application of
normalization and filtering techniques. By using PRAAT              F6: Jitter (local)                    0.3647     0.1806      0.0912

software the goal is to describe the signal in terms of             F7: Jitter (local,   0.142591959
                                                                                                          0.2179     0.1710      0.0883
some of its fundamental components. Input to the                    absolute)

PRAAT is a cry signal, and its output is a vector of                F8: Jitter (rap)
                                                                                                          0.3674     0.1476      0.0663
features that characterizes the key elements of the cry's
sound wave.                                                         F9: Jitter (ppq5)                     0.3524     0.1426      0.0599

           We     have   constructed    Knowledge      Base                              0.328625606
                                                                    F10: Jitter (ddp)                     0.3674     0.1476      0.0663
employing the features of healthy samples of infant cries
by removing the out layer values, which is presented in             F11: Shimmer
                                                                                                          0.3142     0.1826      0.1043
Table 1. Obviously the strength of the knowledge
                                                                    F12:Shimmer          0.042289
derived depends upon the size m. It is based on Mean                                                      0.1970     0.2127      0.1549
                                                                    (local, dB)
(µ) and Variance (σ2) parameters of the features of the             F13: Shimmer         0.264902
                                                                                                          0.3535     0.1706      0.0955
samples. The knowledge base consists of a pair of
parameters- mean (µ) and variance (σ2), for each feature            F14: Shimmer         0.24904
                                                                                                          0.3448     0.1520      0.0969
of a set of healthy samples. Generally in supervised
                                                                    F15 :Shimmer         0.189669
                                                                                                          0.2718     0.1414      0.0849
classification, the feature values are compared with the            (apq11)

mean values of the feature set of control samples, and                                   0.264983
                                                                    F16:Shimmer (dda)                     0.3540     0.1451      0.0906
subsequently the variance component is helpful for the
                                                                    F17: Mean            0.678782
analysis of error made by the classifier. A distance                                                      0.5931     0.1987      0.1017
measure, called Doyle’s distance measure is employed to               Net Doyle’s Distance Components of Healthy Infant cry      1.5412

quantify the distance that the test sample holds with the
reference base. Doyle’s distance model utilizes both                   Table 1: Doyle’s distance values for the Healthy sample
mean and variance parameters to compute the distance                                        size = m+ m = 70

                                                                                                   ISSN 1947-5500
                                                              (IJCSIS) International Journal of Computer Science and Information Security,
                                                                                                                        Vol. 8, No.2, 2010

TABLE II                                                                    with the previous researchers, who also had identified
                                                                            the same parameters for discrimination of the samples
                                               Doyle’s Distance
                       Doyle’s Distance
         Element                               Components                   that is both healthy and unhealthy cry in infants.
                                               of Unhealthy                           Thus it results that higher affiliation index or
                       of Healthy Infant cry
                                               Infant cry
                                                                            Doyle’s distance value because of an unhealthy sample
F1:Median pitch        0.0466                  0.2309
                                                                            indicates that the sample is refuted by the reference base.
F2 :Mean pitch         0.0579                  0.2797
                                                                            Therefore this method is a simple method to model a
F3 : Minimum pitch     0.1648                  0.3215
                                                                            reference base in terms of Mean – Standard deviation as
F4 : Maximum pitch     0.0605                  0.0761
F5 : Degree of voice
                                                                            knowledge parameters is suggested. Doyle’s distances
                       0.1107                  0.0674
breaks                                                                      are computed for affiliation analysis of a test sample.
F6 : Jitter (local)    0.0912                  0.1521                       This work creates lot of scope for further improvements.
F7 : Jitter (local,    0.0883                  0.0901
F8 : Jitter (rap)      0.0663                  0.1526
                                                                               The authors wish to thank to Dr. N.P. Nataraja,
F9: Jitter (ppq5)      0.0599                  0.1469
                                                                            Director, JSS Institute of Speech and Hearing for
F10: Jitter (ddp)      0.0663                  0.1526
                                                                            providing all the necessary resource information,
F11: Shimmer (local)   0.1043                  0.9250
F12 Shimmer
                       0.1549                  0.7784
(local, dB)                                                                 REFERENCES
F13: Shimmer (apq3)    0.0955                  0.7340
                                                                            [1] Liisi Rautava , Asta Lempinen , Stina Ojala , Riitta
F14: Shimmer (apq5)    0.0969                  0.9060                           Parkkola, “Acoustic quality of cry in very-low-
F15 Shimmer (apq11)    0.0849                   1.0754
                                                                                birth-weight infants at the age of 1 1/2 years,“
                                                                                March 2006.
F16 Shimmer (dda)      0.0906                  0.7551                        [2] Sanjay Pande, PhD Thesis “An algorithmic model
F17: Mean
                                                                                 for exploratory analysis of trace elements in
                       0.1017                  0.2180                            cognition and recognition of neurological
                                                                                 disorders,”, under the guidance of Dr. P
Total Distance                                 7.0618                            Nagabhushan, Department of studies in computer
                                                                                 Science. University of Mysore,2004.
                                                                             [3] Kathleen Wermke, Ph.D., Christine Hauser,
  Table 2: Comparison of distance between Healthy and
                                                                                 D.D.S., Gerda Komposch, D.D.S., Ph.D., and
                Unhealthy infant cries
                                                                                 Angelika Stellzig, D.D.S., Ph.D. “Spectral Analysis
CONCLUSION                                                                       of Prespeech Sounds (Spontaneous Cries) in Infants
                                                                                 With Unilateral Cleft Lip and Palate (UCLP): A
The randomly chosen sample from healthy knowledge                                Pilot Study ,“July 1, 2001.
base of infant cry was replicated m + m = 2m = 70 and                       [4] R. G. Barr, B. Hopkins and J. A. Green. “Crying as
                                                                                 a Sign, a Symptom, and a Signal”, Mac Keith Press,
Doyle’s Distance value was computed which is tabulated                           London, 2000.
in Table 1.                                                                 [5] M. Sc Thesis “Analysis of Infant Cry,” under the
                                                                                 Guidance of Dr. N.P Nataraja, 1998.
From the table 2 it can be easily understood that the                       [6] Lummaa V., Vuorisalo T., Barr R. G. and Lehtonen
parameters such as Minimum pitch, Jitter,               Shimmer                  L. “Why Cry? Adaptive Significance of Intensive
                                                                                 Crying in Human Infants,” Evolution and Human
vary in case on unhealthy samples and also it is observed                        Behavior, vol. 19 (3), pp. 193 – 202, May 1998.
that the summation is approximately 4.5 times more in                        [7] Michelsson K., Christensson K., Rothganger H. and
                                                                                 Winberg J., "Crying in separated and non-
case of unhealthy samples further it is clear that the                           separated newborns: sound spectrographic
method of Doyle’s distance will provide a insight in                             analysis", Acta Pediatr, vol. 85 (4), pp. 471 – 475,
                                                                                 April 1996.
mining a data base since our results are in accordance

                                                                                                     ISSN 1947-5500
                                                      (IJCSIS) International Journal of Computer Science and Information Security,
                                                                                                                Vol. 8, No.2, 2010

[8] Gilbert H. R. and Robb M. P., “Vocal fundamental
     frequency characteristics of infant hunger cries:
     birth to 12 months, “Int J Pediatr Otorhinolaryngol,
     vol. 34, pp. 237 – 243 1996.
[9] Barbara F. Fuller , Maureen R. Keefe , Mary Curtin
     “Acoustic Analysis of Cries from Normal and
      Irritable Infants,“ Western Journal of Nursing
      Research, Vol. 16, No. 3, 243-253 (1994).
[10] QUICK Zoe L.; ROBB Michael P.;
      WOODWARD Lianne J. “Acoustic cry
      characteristics of infants exposed to methadone
       during pregnancy ,“ Acta pediatric ISSN 0803-
 [11] Hartmut Rothganger, L. Wolfgang, auudge, E.
      Ludwig Grauel, ”Jitter-index of the fundamental
      frequency of infant cry as a possible diagnostic tool
      to predict future developmental problems, “1990.
 [12] Lieberman P., Harris K.S., Wolff P. & Russell L.H.
      (1971),” New born infant cry and non human
      primate vocalization”, Journal of Speech and
      Hearing Research, 14(4) 710.
[13] Golub, H.L (1979),” A Physio acoustic model of
      the infant cry and its use for medical diagnosis and
      prognosis,” In J.J Wolf and D.H Klatt (Eds.),
      Speech Communication Papers Presented at the
      97th Meeting of the Acoustical Society of America.
      Cambridge, MA., Acoustical Society of America.

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