45 results about "Resting state eeg" patented technology

The present invention provides a health care support system that can give appropriate advice depending on a situation.At first step, whether a driver is seated is checked using a signal from a pressure sensor. At second step, whether the driver is in a resting state is checked using heart rate and the like. At third step, physical information is acquired. At forth step, a health status is judged based on the measured pieces of physical information and the like. At fifth step, activity status information is acquired. At sixth step, an activity status is judged based on the activity status information. At seventh step, an appropriate piece of advice for the driver is selected based on a judgment result of the health status and a judgment result of the activity status. At eighth step, the selected piece of advice is displayed on a displaying section and audibly outputted.

The present invention provides apparatus and methods for improving satellite navigation by assessing the dynamic state of a platform for a satellite navigation receiver and using this data to improve navigation models and satellite tracking algorithms. The dynamic state of the receiver platform may be assessed using only accelerometer data, and does not require inertial navigation system integration. The accelerometers may not need to be very accurate and may not need to be aligned and / or accurately calibrated. A method of accelerometer assisted satellite navigation may comprise: detecting a stationary condition of an accelerometer set; gross-calibrating the accelerometer set when in the stationary condition, wherein gross-calibrating includes determining a combined-bias of the accelerometer set; defining at least two acceleration levels using the combined-bias; collecting accelerometer data; categorizing the accelerometer data into one of the acceleration levels; and utilizing the categorized accelerometer data to enhance satellite navigation.

A non-contact method for detecting physiological signals and motion in real time comprises: sensing a portion of a human body to generate a series of image frames by an optical sensing element; determining a complexion region from each of the image frames; then calculating a central coordinate of the complexion region; determining a sample block by expanding a surrounding range from the central coordinate, for getting a complexion fluctuation waveform; comparing said central coordinate with a central coordinate of a later image frame, to calculate a displacement in a unit time for determining whether the portion of the human body is in a static state. In the static state, an operating unit performs noise filter and peak detecting for complexion fluctuation waveform, and calculates a physiological signal. Said method can reduce the amount of data required to be processed in physiological signal detection, and improve the accuracy of the detection.

A method of optimizing inter-site delay is disclosed for a cardiac rhythm management device that includes a dual chamber pacemaker, especially designed for treating congestive heart failure by pacing a plurality of sites. A microcontroller is operative to adjust the pacing mode and inter-site delay of the pacemaker so as to achieve optimum hemodynamic performance. Atrial cycle lengths measured during transient (immediate) time intervals following a change in the mode inter-site delay are signal processed and a determination can then be made as to which particular configuration yields the optimum performance. Performance is optimized when the patient is at rest and when the patient exercises so that a rate-adapted dynamic value of the optimum performance can be applied.

The invention discloses a mathematics supernormal teenager brain functional connection network analysis method based on resting state EEG signals. The method comprises: based on a resting state EEG signal, using a phase lag algorithm based on Wilcoxon signed-rank test (PLWT) to establish a connection network, so as to measure the connection network using graph theory indexes, and depicting connection network characteristics of mathematics supernormal teenagers, including active brain regions and graph theory indexes. Compared with the prior art, the method has the following advantages: comparing the connection network characteristics of mathematics supernormal teenagers, depicted based on the resting state EEG signals, with that based on task state EEG signal analysis, obtained characteristics are simpler and more universal, and the applied PLWT method performs phase synchronization determination of EEG signals by a Wilcoxon signed-rank test framework, to explore internal connection network, prevent subjective setting of a threshold value, and reduce undetermined factors in the connection network analysis.

A system and method for measuring a functional lateralization of a subject brain is provided. The method includes providing a set of functional magnetic resonance imaging (fMRI) data acquired during a resting state of a subject, and selecting a plurality of seed voxels associated with locations in hemispheres of a brain of the subject. The method also includes determining a degree of within-hemisphere connectivity for each seed voxel using the fMRI data, determining a degree of cross-hemisphere connectivity for each seed voxel using the fMRI data, and computing an autonomy index for each seed voxel using the degree of within-hemisphere connectivity and the degree of cross-hemisphere connectivity, wherein the autonomy index is indicative of a connectivity asymmetry between the hemispheres. The method further includes generating a report indicative of a specialization profile determined for a region of interest in the brain of the subject.

The invention discloses a target motion and rest state judging method based on the passive multi-point positioning technology. The method can perform judgment through a signal measured value or multiple measured values. The judgment step with the signal measured value comprises computing the geometric accuracy factor matrix of the single measured value and utilizing the geometric accuracy factor matrix to normalize the measured value to obtain a judgment statistic. The judgment step with the multiple measured values comprises subtracting the N-1th measured value from the Nth measured value, composing a column vector according to x-axis data and y-axis data, structuring an associated matrix of the vector by combining with the geometric accuracy factor matrix computed from the measured values to normalize the column vector and further to structure a judgment statistic, and performing judgment according to a threshold value. The target motion and rest state judging method based on the passive multi-point positioning technology is based on statistical hypothesis testing and combined with an airport surface monitoring multi-point location system, thereby being high in system flexibility and robustness, small in calculating amount, good in detecting performance and capable of performing judgment flexibly through the single measured value and the multiple measured values.

The invention is suitable for the technical field of EEG signal processing, and provides a method and apparatus for extracting features from resting state EEG data. The method comprises the followingsteps: obtaining a EEG signal segment of a subject in the resting state, and calculating a global energy spectrum corresponding to the EEG signal segment; determine a micro-state corresponding to eachtime point in the EEG signal segment according to the global energy spectrum to obtain a micro-state sequence; and using a sliding time window algorithm to describe the micro-state sequence, and using micro-states whose duration are greater than a first time threshold in a first micro-state sequence sub-segment as main features of the first micro-state sequence sub-segment to obtain a characteristic sequence, wherein the first micro-state sequence sub-segment is a micro-state sequence sub-segment described by the current sliding time window. The technical solution provided by the invention uses the sliding time window algorithm to describe the micro-state sequence, can improve the effectiveness of the obtained feature sequence, reduces the amount of calculation, and reduces the influenceof noises on the data.

Over 350 million people worldwide suffer from depression, a third of whom are medication resistant. Seizure therapy remains the most effective treatment in depression, even when many treatments fail. The utility of seizure therapy is limited due to its cognitive side effects and stigma. The biological targets of seizure therapy remain unknown, hindering design of new treatments with comparable efficacy. Seizures impact the brains temporal dynamicity observed through electroencephalography. This dynamicity reflects richness of information processing across distributed brain networks subserving affective and cognitive processes. We investigated the hypothesis that seizure therapy impacts mood (depressive symptoms) and cognition by modulating brain temporal dynamicity. We obtained resting-state EEG from thirty-four patients (age=46.0±14.0, 21 females) receiving two types of seizure treatments—electroconvulsive therapy or magnetic seizure therapy. We employed multi-scale entropy to quantify the complexity of brain's temporal dynamics before and after seizure therapy. We discovered that reduction of complexity in fine time scales underlined successful therapeutic response to both seizure treatments. Greater reduction in complexity of fine time scales in parieto-occipital and central brain regions was significantly linked with greater improvement in depressive symptoms. Greater increase in complexity of coarse time scales was associated with greater decline in cognition including the autobiographical memory. These findings were region- and time-scale specific. That is, change in complexity in occipital regions (e.g., O2 electrode or right occipital pole) at fine time-scales was only associated with change in depressive symptoms, and not change in cognition, and change in complexity in parieto-central regions (e.g., Pz electrode or intra and transparietal sulcus) at coarser time-scale was only associated with change in cognition, and not depressive symptoms. Finally, region and time-scale specific changes in complexity classified both antidepressant and cognitive response to seizure therapy with good (80%) and excellent (95%) accuracy, respectively. In this study, we discovered a novel biological target of seizure therapy; complexity of the brain resting-state dynamics. Region and time-scale dependent changes in complexity of the brain resting-state dynamics is a novel mechanistic marker of response to seizure therapy that explains both the antidepressant response and cognitive changes associated with this treatment. This marker has tremendous potential to guide design of the new generation of antidepressant treatments.

The invention discloses a target motion and rest state judging method based on the passive multi-point positioning technology. The method can perform judgment through a signal measured value or multiple measured values. The judgment step with the signal measured value comprises computing the geometric accuracy factor matrix of the single measured value and utilizing the geometric accuracy factor matrix to normalize the measured value to obtain a judgment statistic. The judgment step with the multiple measured values comprises subtracting the N-1th measured value from the Nth measured value, composing a column vector according to x-axis data and y-axis data, structuring an associated matrix of the vector by combining with the geometric accuracy factor matrix computed from the measured values to normalize the column vector and further to structure a judgment statistic, and performing judgment according to a threshold value. The target motion and rest state judging method based on the passive multi-point positioning technology is based on statistical hypothesis testing and combined with an airport surface monitoring multi-point location system, thereby being high in system flexibility and robustness, small in calculating amount, good in detecting performance and capable of performing judgment flexibly through the single measured value and the multiple measured values.

A blood pressure measurement device measures a pulse period of a patient and includes a memory, a threshold calculation section, a rest / unrest condition determination section, and a display unit. The memory stores data of the measured pulse period and data of a pulse period of past measurement of the patient. The threshold calculation section calculates a threshold value range based on the data of the pulse period of the past measurement of the patient. The rest / unrest condition determination section determines whether the patient was under the rest condition or the unrest condition during blood pressure measurement by comparing the measured pulse period with the threshold value range. The display unit displays the blood pressure measured and whether the blood pressure was measured when the patient was in the rest condition or the unrest condition.

The movement of skin on an animated target, such as a character or other object, is simulated via a simulation software application. The software application creates a finite element model (FEM) comprising a plurality of finite elements based on an animated target. The software application attaches a first constraint force to a node associated with a first finite element in the plurality of finite elements. The software application attaches a second constraint force to the node. The software application detects a movement of the first finite element that results in a corresponding movement of the node. The software application determines a new position for the node based on the movement of at least one of the first finite element, the first constraint force, and the second constraint force.