Abstract: A data collection device according to an aspect of the present disclosure includes: at least one memory storing a set of instructions; and at least one processor configured to execute the set of instructions to: detect a target data point that is a data point at which a target is observed in acoustic data obtained by observation of the target; determine an analysis range in the acoustic data based on the target data point; detect an abnormality in the analysis range; and output information of the analysis range in which the abnormality is detected.

Abstract: A lung sound analysis system includes an acquisition means for acquiring time-series acoustic signals including lung sounds of a heart failure patient, a detection means for detecting abnormal lung sounds from the acquired time-series acoustic signals, an observation acquisition means for transmitting, to a terminal device of a medical specialist, analysis object lung sound information in which the acquired time-series acoustic signals and a result of the detection are associated with each other, and receiving, from the terminal device, analysis object lung sound information to which an observation by the medial specialist on the time-series acoustic signals is added, and a generation means for generating learning data for detecting abnormal lung sounds on the basis of the analysis object lung sound information to which the observation by the medial specialist is added.

Abstract: A trajectory estimation device that includes a waveform generation unit that generates, by using signals based on waves detected by at least three sensors, peak waveforms consisting of time series data of peak frequencies of the signals, a parameter estimation unit that estimates, from the peak waveforms relating to the waves detected by the at least three sensors, a trajectory parameter relating to a trajectory of a moving body having a wave source of the waves, and a trajectory estimation unit that estimates, for all combinations of two of the peak waveforms selected from among combinations of at least three of the peak waveforms, a wave source direction candidate for each of the waves by using the trajectory parameter, and estimate, as a trajectory of the moving body, overlapping trajectory candidates from among trajectory candidates estimated based on the wave source direction candidates.

Abstract: An analysis device includes a detection unit that detects abnormality in lung sounds for each of auscultation positions on the basis of time-series acoustic signals including lung sounds of each of the auscultation positions; a determination unit that determines severity of heart failure of a patient on the basis of a detection result of abnormality in the lung sounds of each of the auscultation positions detected by the detection unit and condition information representing a condition of the patient; and an output unit that decides whether or not to output predetermined information to an external device on the basis of a result of determination by the determination unit, and performs output corresponding to a result of decision.

Abstract: A lung sound analysis system includes a storage means for storing therein the history of auscultation observations on lung sound data of each of auscultation positions of a subject who is a heart failure patient, a calculation means for calculating appearance frequency of abnormal sounds for each of the auscultation positions on the basis of the history, a determination means for determining the sequence of the auscultation positions at which lung sounds are to be auscultated from the subject, on the basis of the calculated appearance frequency, and an acquisition means for giving guidance on the auscultation positions of the subject to an operator according to the determined sequence, and acquiring time-series acoustic signals including lung sounds from a guided auscultation position.

Abstract: An analysis device includes a detection unit that detects abnormality in lung sounds for each of auscultation positions on the basis of time-series acoustic signals including lung sounds of each of the auscultation positions; a determination unit that determines severity of heart failure of a patient on the basis of a detection result of abnormality in the lung sounds of each of the auscultation positions detected by the detection unit and condition information representing the condition of the patient; and a decision unit that decides an instruction to be output to the patient on the basis of a result of the determination by the determination unit.

Abstract: A lung sound analysis system includes an acquisition means for acquiring time-series acoustic signals including lung sounds of a subject who is a heart failure patient, a determination means for determining a pause phase of breathing of the subject, a dividing means for dividing the time-series acoustic signals into those in a period of the pause phase of breathing of the subject and those in a period other than the pause phase, according to a result of the determination, and a detection means for detecting abnormality in the lung sounds from the time-series acoustic signals in the period other than the pause phase after the division.

Abstract: A lung sound analysis system includes an acquisition means for acquiring time-series acoustic signals including lung sounds of a subject who is a heart failure patient, a determination means for determining a pause phase of breathing of the subject, a dividing means for dividing the time-series acoustic signals into those in a period of the pause phase of the subject and those in a period other than the pause phase, according to a result of the determination, a calculation means for calculating an index value representing the quality of the time-series acoustic signals in the period other than the pause phase, from the intensity of the time-series acoustic signals in the period of the pause phase and the intensity of the time-series acoustic signals in the period other than the pause phase after the division, and a warning means for giving warning based on the calculated index value.

Abstract: In order to estimate the trajectory of a moving wave source, this trajectory estimation device (10) comprises: an acquisition unit (11) that acquires wave motion data based on wave motion detected by a plurality of sensors (100); a generation unit (12) that generates a spectrogram using the wave motion data; an extraction unit (13) that extracts a Doppler shift from the spectrogram; a selection unit (14) that selects, as a sensor pair, two sensors that satisfy a preset selection condition pertaining to the Doppler shift; and an estimation unit (15) that estimates the trajectory of a wave source, which is the source generating the wave motion, on the basis of the positional relationship between the sensors constituting the sensor pair and the relationship of the Doppler shift between the two sensors constituting the sensor pair.

Abstract: A wave source direction estimation device includes a signal extraction unit that sequentially extracts, one at a time, signals of signal segments according to a set time length from at least two input signals based on a wave detected at different detection positions, a function generation unit that generates a function associating at least two signals extracted by the signal extraction unit, a sharpness calculation unit that calculates sharpness of a peak of the function generated by the function generation unit, and a time length calculation unit that calculates the time length based on the sharpness and set the calculated time length.

Abstract: A wave-source-direction estimation device includes: a plurality of input units that acquires, as input signals, electrical signals based on waves detected by a plurality of sensors; a signal selection unit that selects a plurality of pairs that are each a combination of two input signals from among a plurality of the input signals; a relative delay time calculation unit that calculates, as relative delay times, arrival time differences of the waves at the sensors that are supply sources of the two input signals composing each of the pairs, for each wave source direction; and an integrated-estimated-direction-information calculation unit that generates per-frequency estimated direction information for each of the pairs using the input signals composing each of the pairs and the relative delay times of each of the pairs and generates integrated estimated direction information by assigning a weight to and integrating the estimated direction information on all the pairs.

Abstract: A wave-source-direction estimation device includes: input units that acquire, as input signals, electrical signals that have been converted from waves acquired by sensors; a signal selection unit that selects at least two pairs that are each a combination of at least two input signals from among the input signals; a relative delay time calculation unit that calculates, as relative delay times, arrival time differences of the waves for each wave source searching direction between the at least two input signals composing one of the pairs of the input signals; at least one per-frequency estimated-direction-information generation unit that uses the pairs of the input signals and the relative delay times to generate estimated direction information on a wave source of the waves for each frequency; and an integration unit that integrates the estimated direction information generated for each frequency by the per-frequency estimated-direction-information generation unit.

Abstract: A wave-source-direction estimation device includes: a plurality of input units that acquires, as input signals, electrical signals based on waves detected by a plurality of sensors; a signal selection unit that selects a plurality of pairs that are each a combination of two input signals from among a plurality of the input signals; a relative delay time calculation unit that calculates, as relative delay times, arrival time differences of the waves at the sensors that are supply sources of the two input signals composing each of the pairs, for each wave source direction; and an integrated-estimated-direction-information calculation unit that generates per-frequency estimated direction information for each of the pairs using the input signals composing each of the pairs and the relative delay times of each of the pairs and generates integrated estimated direction information by assigning a weight to and integrating the estimated direction information on all the pairs.

Abstract: Even a small sound for which a change in a histogram is small can be accurately detected. A signal detection device includes signal input means for inputting signals acquired by a plurality of sensors, cross-correlation function calculation means for calculating cross-correlation functions for each predetermined number of samples, based on the signals, and background noise model derivation means for deriving a background noise model, based on the cross-correlation functions; and detection means for detecting a change in the signals, based on comparison of values of the cross-correlation functions with the background noise model.

Abstract: A vibration source estimation device, method and computer-readable medium are provided. The vibration source estimation device comprises a processor configured to execute instructions to receive data samples of a plurality of vibration signals generated at a vibration position, the data samples being associated with a plurality of frames. The processor is also configured to execute instructions to calculate a cross correlation function for each frame based on the data samples, calculate a weight for each frame based on a signal-to-noise ratio calculated from the cross correlation function, multiply the cross correlation function for each frame by the weight, calculate a sum of weighted cross correlation functions for respective frames as a weighted-cross-correlation function, and estimate the vibration position based on the weighted-cross-correlation function.

Abstract: A vibration source estimation device, method and computer-readable medium are provided. The vibration source estimation device comprises a processor configured to execute instructions to receive data samples of a plurality of vibration signals generated at a vibration position, the data samples being associated with a plurality of frames. The processor is also configured to execute instructions to calculate a cross correlation function for each frame based on the data samples, calculate a weight for each frame based on a signal-to-noise ratio calculated from the cross correlation function, multiply the cross correlation function for each frame by the weight, calculate a sum of weighted cross correlation functions for respective frames as a weighted-cross-correlation function, and estimate the vibration position based on the weighted-cross-correlation function.