Biomedical subjects

T Grönfors

Publications and source records attributed to T Grönfors.

11 recordsLinked to original sources

PubMed2002

Hippocampus retains the periodicity of gamma stimulation in vivo.

Several behavioral state dependent oscillatory rhythms have been identified in the brain. Of these neuronal rhythms, gamma (20-70 Hz) oscillations are prominent in the activated brain and are associated with various behavioral functions ranging from sensory binding to memory. Hippocampal gamma oscillations represent a widely studied band of frequencies co-occurring with information acquisition. However, induction of specific gamma frequencies within the hippocampal neuronal network has not been satisfactorily established. Using both in vivo intracellular and extracellular recordings from anesthetized rats, we show that hippocampal CA1 pyramidal cells can discharge at frequencies determined by the preceding gamma stimulation, provided that the gamma is introduced in theta cycles, as occurs in vivo. The dynamic short-term alterations in the oscillatory discharge described in this paper may serve as a coding mechanism in cortical neuronal networks.

Animals↗

PubMed2000

Lossy compression of auditory brainstem response signals.

Compression of digital signals is frequently utilised in numerous applications like music and speech signals. So far compression of biomedical signals has concentrated almost purely on electrocardiography. We recently opened compression studies on biomedical signals concerning otological measurements performed in accord with hearing and balance problems of humans. In this paper we shall present results for auditory brainstem response signals gained with traditional and modern compression methods as well as one of ours.

Brain Stem↗

PubMed1997

Latency estimation of auditory brainstem response by neural networks.

In the clinical application of auditory brainstem responses (ABRs), the latencies of five to seven main peaks are extremely important parameters for diagnosis. In practice, the latencies have mainly been done by manual measurement so far. In recent years, some new techniques have been developed involving automatic computer recognition. Computer recognition is difficult, however, since some peaks are complicated and vary a lot individually. In this paper, we introduce an artificial neural network method for ABR research. The detection of ABR is performed by using artificial neural networks. A proper bandpass filter is designed for peak extraction. Moreover, a new approach to estimate the latencies of the peaks by artificial neural networks is presented. The neural networks are studied in relation to the selection of model, number of layers and number of neurons in each hidden layer. Experimental results are described showing that artificial neural networks are a promising method in the study of ABR.

Evoked Potentials, Auditory, Brain Stem↗

PubMed1996

Segmentation of auditory brainstem response signals.

Auditory brainstem responses are used to detect hearing defects in audiology and otoneurology. The use of computer programs for the analysis of such recordings is increasing. To identify their detailed properties a pattern recognition algorithm implemented in an analysis program must be highly reliable. For the recognition process, some preprocessing phases after recording the necessary, such as filtering and often also segmentation. In the following, we will explore segmentation, which can be used in preprocessing of biomedical signals after filtering. We studied linear segmentation, where slopes of short signal segments are computed and divided into different classes according to their values. A segment length of 8 samples for a sampling frequency of 50 kHz employed was best according to our tests and error criteria. Using clustering, we found that less than 10 segment classes is suitable for pattern recognition.

Algorithms↗

PubMed1995

Effect of sampling frequencies and averaging resolution on medical parameters of auditory brainstem responses.

The amplitude ratio and latency between peaks of the auditory brainstem response are widely used as medical parameters of response in the clinical assessment. Several methodological factors affect the medical parameters. The sampling frequency, the resolution of the averager and filtering of the signal are important factors. Typically the signal is highly over-sampled in the recording phase. The resolution of the averager should be as good as possible to ensure adequacy of the amplitude parameter. The latency parameter is more tolerant to the reduction of the sampling frequency, and the signal can be decimated down to 10 kHz to reduce computational complexity.

Acoustic Stimulation↗

PubMed1995

Vestibular evoked responses in man: methodological aspects.

We have developed a stimulation method where the subject is sitting and the head is rotated with shock bursts elicited by a shaker with a repetition rate of 2 Hz. The head movement is monitored with an accelerometer mounted on the cheek by a head band. The maximum amplitude of the head movement is 3 degrees. The electrodes were places on vertex with a negative electrode on the mastoid. During stimulation, 90 dB white noise was applied to the ears to mask the noise generated by the stimulus. We recorded following responses: i) VER from ipsilateral ear, ii) VER from contralateral ear, iii) eye movement with EOG, and iv) movement of the head. Amplification and averaging of the signal were made with an evoked response recorder (Nihon Kohden, Neuropac four). From 200 to 2,000 averaged responses were collected and stored for further analysis on a floppy disc. During second stage filtering the data were fed into a microcomputer where appropriate programs were used to eliminate the EMG and movement artifacts.

Acceleration↗

PubMed1993

Identification of auditory brainstem responses.

Auditory brainstem evoked responses are routinely used in audiology and otoneurology. An automatic method can be used to roughly classify the responses into probably normal, probably abnormal, and uncertain cases. Interpretation of the auditory brainstem response is a multistage process. Essential tasks are to detect individual peaks in the waveform and to choose representatives examples as medically interesting Jewett components. Our method is based on the comparison of detected peaks and normal values by means of an evaluation function, choosing representatives so that the values of this function will be maximized. We have studied the effects of some evaluation functions on the ability to correctly classify an evoked response. It turns out that the choice of an appropriate evaluation function is crucial in some problematic cases.

Adolescent↗

PubMed1993

Peak identification of auditory brainstem responses with multi-filters and attributed automaton.

An attributed automaton, a special case of attribute grammar, is a flexible tool in pattern recognition. It allows the utilization of contextual information from previously analyzed patterns in the analysis of the current pattern, and offers the possibility of describing those structural characteristics of patterns which cannot be described by classic methods of syntactic pattern recognition. Auditory brainstem responses are routinely used in audiology and otoneurology. Many studies on using the spectral analysis of averaged auditory brainstem responses have described at least two frequency bands, corresponding to the slow and fast components. Selective non-recursive digital filters for each frequency band in the spectrum of the auditory brainstem response have revealed enhancement or attenuation of components, depending on the band. In this study, multi-filters and an attributed automaton were combined for the identification of peaks.

Adolescent↗

PubMed1992

Evaluation of some nonrecursive digital filters for signals of auditory evoked responses.

Auditory brain stem evoked responses are routinely used in audiology and otoneurology. Because recordings include more or less noise, the signals of evoked responses need digital filtering to suppress the noise. Nonrecursive digital filters are often the best since they can be organized to have no phase shift, which is essential in order not to distort sensitive parameters, as latency, in evoked responses. We have studied effects of some nonrecursive digital filters on the latency parameters of evoked responses. It turned out that digital filtering can have considerable influence on latencies, and thus the choice of appropriate filters is crucial.

Evaluation Studies as Topic↗

PubMed1991

A microcomputer system for assessment of peripheral blood flow. An example of nasal blood flow.

We have designed and implemented a microcomputer system for studying the effect of various mediator substances on the nasal blood flow. The system uses an IBM PC/AT microcomputer, which is connected with a Laser Doppler Flowmeter (LDF) and an iontophoretic drug application system. The LDF measures flux from the tissue that in the example is the inferior nasal turbinate. The flux is converted to digital form by an analog-digital converter of 12 bits. The program is implemented in the Pascal language. In the analysis, a flux level, amplitude, rise time and decay time of the pulse wave are determined. The effect of drugs on the flux can be studied by applying them iontophoretically. In the program the length and number of the drug application periods as well as the recording period are user-driven. In the nasal blood flow iontophoretically administered adrenaline reduced significantly the flux parameters and histamine canceled this effect. Tachyphylalaxis was a frequent observation in repeated measurements. The system can be used to evaluate the role of different transmitters in the etiology of chronic rhinitis.

Adult↗

PubMedDate not supplied

Vector quantization as a method for integer EMG signal compression.

Vector quantization (VQ) is a well-known lossy compression method, which has not often been applied to biosignals. In this paper, VQ and its mean residual variant for encoding and decoding electromyography (EMG) signals have been tested. The methods are selected in such a way that they can be later applied in a low-resource embedded system. A neural network approach is used for codebook generation. The preservation of medical parameters is a prominent sign of quality in medical compression systems. Both signal level fidelity factors and preserving medical parameters are tested. The results show that mean residual vector quantization with short segments is a workable approach for EMG signal compression.

Algorithms↗