OPTIMI: Early Prediction and Prevention of Depression

Institute for Response-Genetics, Departement of Psychiatry (KPPP)

Psychiatric Hospital, University of Zurich


MSELECT — Selects speech parameters and/or psychopathology scales

This program is used to define a subsample of cases for subsequent analyses. Cases are selected through the specification of study-numbers, group-numbers, proband-numbers, recording days, and experimental conditions. A sequence of CSELECT-calls accumulates cases, so that any problem-specific subsample of cases can be assembled by a sequence of single steps. An existing subsample of cases is deleted by means of the parameter RSET.

            Specificationlist:     MSELECT
            I4 SCAL                      1  Default-value
            I4 PROT                      0  Default-value
            I4 RSET                      1  Default-value
            01 SCAL Selects scale/instrument
            02 PROT Controls output to display/printer
            03 RSET Controls concatenation of cases
            04 DEMO Examples that illustrate program function
            - SCAL = 1: Speech parameters
                   = 2: Zurich Health Questionnaire (ZGF)
                   = 3: Coping Behavior (COPE)
                   = 4: Hamilton Depression Scale (HAMD)
                   = 5: Positive and Negative Symptom Scale (PANSS)
                   = 6: Syndrome Check List (SSCL16)
                   = 7: Syndrome Check List Axis V (SSCL16S)
            - PROT = 0: No print output
                     1: Report of all selected instruments
            - RSET = 0: Add instrument to list
                   = 1: Begin new list
            - DEMO: Selecting scales for analysis (Speech, PANSS, HAMD, COPE)


            &&START MSELECT=Normative speech study zurich (study 600)
            &&START MSELECT=Normative speech study zurich (study 600)
            &&START MSELECT=Normative speech study zurich (study 600)
            &&START MSELECT=Normative speech study zurich (study 600)
            &&START MSELECT=Normative speech study zurich (study 600)
Fig. 13: Voice sound characteristics possess a distinct "individuality" that allows one, for example, to identify persons on the phone very quickly without speaking explicitly about the identity of the speaker. In fact, voice sound characteristics have a strong biological component in the range of 80% or higher. The inter-individual differences of voice sound patterns between unrelated subjects can be studied in detail by means of a similarity function that quantifies between-subject similarities and dissimilarities as a function of frequency (here: comparison of two unrelated subjects). See Fig. 14 for a comparison of repeated assessments on the same individual at 14-day intervals.

Everis, Spain
ETH, Switzerland
UZH, Switzerland
Freiburg, Germany
MA Systems, UK
Bristol, UK
Xiwrite, Italy
Ultrasis, UK
Jaume, Spain
Valencia, Spain
Lanzhou, China


EU-Grant (FP7):

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