Biomaterial Database

Spectral analysis of the EEG: comparison of various spectral parameters. 1981

P Matthis, and D Scheffner, and C Benninger

One of the main problems in spectral analysis of the EEG consists of finding relevant parameters which are capable of summarizing all information included in the power spectrum. The mathematical properties and the clinical applicability of 4 sets of parameters were compared: (1) percentage of power within the conventional frequency ranges, (2) mobility and complexity (Hjorth), (3) the slope parameter (Dumermuth), (4) the coefficients of the autoregressive model. They were applied to the EEG changes in a child with brain stem tumour during cerebral radiotherapy. The statistical analysis suggests: (I) there are only minor differences in describing the EEG course between the conventional frequency ranges, mobility and the slope parameter, (II) the complexity is less satisfactory, (III) the first autoregressive coefficient of the AR model yields the best results.

UI	MeSH Term	Description	Entries
D012044	Regression Analysis	Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable.	Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D001932	Brain Neoplasms	Neoplasms of the intracranial components of the central nervous system, including the cerebral hemispheres, basal ganglia, hypothalamus, thalamus, brain stem, and cerebellum. Brain neoplasms are subdivided into primary (originating from brain tissue) and secondary (i.e., metastatic) forms. Primary neoplasms are subdivided into benign and malignant forms. In general, brain tumors may also be classified by age of onset, histologic type, or presenting location in the brain.	Brain Cancer,Brain Metastases,Brain Tumors,Cancer of Brain,Malignant Primary Brain Tumors,Neoplasms, Intracranial,Benign Neoplasms, Brain,Brain Neoplasm, Primary,Brain Neoplasms, Benign,Brain Neoplasms, Malignant,Brain Neoplasms, Malignant, Primary,Brain Neoplasms, Primary Malignant,Brain Tumor, Primary,Brain Tumor, Recurrent,Cancer of the Brain,Intracranial Neoplasms,Malignant Neoplasms, Brain,Malignant Primary Brain Neoplasms,Neoplasms, Brain,Neoplasms, Brain, Benign,Neoplasms, Brain, Malignant,Neoplasms, Brain, Primary,Primary Brain Neoplasms,Primary Malignant Brain Neoplasms,Primary Malignant Brain Tumors,Benign Brain Neoplasm,Benign Brain Neoplasms,Benign Neoplasm, Brain,Brain Benign Neoplasm,Brain Benign Neoplasms,Brain Cancers,Brain Malignant Neoplasm,Brain Malignant Neoplasms,Brain Metastase,Brain Neoplasm,Brain Neoplasm, Benign,Brain Neoplasm, Malignant,Brain Neoplasms, Primary,Brain Tumor,Brain Tumors, Recurrent,Cancer, Brain,Intracranial Neoplasm,Malignant Brain Neoplasm,Malignant Brain Neoplasms,Malignant Neoplasm, Brain,Neoplasm, Brain,Neoplasm, Intracranial,Primary Brain Neoplasm,Primary Brain Tumor,Primary Brain Tumors,Recurrent Brain Tumor,Recurrent Brain Tumors,Tumor, Brain
D002648	Child	A person 6 to 12 years of age. An individual 2 to 5 years old is CHILD, PRESCHOOL.	Children
D004569	Electroencephalography	Recording of electric currents developed in the brain by means of electrodes applied to the scalp, to the surface of the brain, or placed within the substance of the brain.	EEG,Electroencephalogram,Electroencephalograms
D005260	Female		Females
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man