Abstract: A method for quantifying swallowing function can include subjecting swallowing segments and non-swallowing segments of vibrational data to processing selected from the group consisting of adaptive trimming, false positive reduction, and a combination thereof. Preferably the vibrational data represents swallowing activity, is from a sensor positioned on the throat of a patient, and is associated with at least one axis selected from the group consisting of an anterior-posterior axis and a superior-inferior axis. Preferably a processing module operatively connected to the sensor performs the processing of the swallowing segments and the non-swallowing segments of the vibrational data. A device comprising a processing module and a sensor such as a single-axis accelerometer or a dual axis accelerometer can perform one or more steps of the method.

Abstract: A method can use dual-axis accelerometry signals obtained during a swallow to classify the swallow as a normal swallow or as an impaired swallow (e.g., an aspiration-penetration). The method can include representing the dual-axis accelerometry signals as meta-features, comparing the salient time and frequency meta-features, identified by regularized binomial logistic regression with elastic net penalty performed on the time and frequency meta-features in a known training data set, with a preset linear discriminant classifier constructed based on the salient meta-features, and classifying the swallow as a normal swallow or a possibly impaired swallow, based on the comparing. Preferably a processing module operatively connected to the sensor performs the processing of the dual-axis accelerometry signals and also automatically classifies the swallow.

Abstract: A method can use dual-axis accelerometry signals obtained during a time period to classify segments of the time period as a cough or as a non-cough artifact (e.g., a rest state, a swallow, a tongue movement, or speech). The method can include representing segments of the dual-axis accelerometry signals as meta-features for each segment of the time period, preferably one or more time features, frequency features, time-frequency features, or information-theoretic features for each segment. The salient meta-features can be used to classify the segments as a cough or a non-cough artifact. Preferably a processing module operatively connected to the sensor performs the processing of the dual-axis accelerometry signals and also automatically classifies the segments. The method and/or the device can be used to diagnose or treat a dysphagia patient, for example by discriminating a cough from a swallow.

Abstract: A method for quantifying swallowing function can include subjecting swallowing segments and non-swallowing segments of vibrational data to processing selected from the group consisting of adaptive trimming, false positive reduction, and a combination thereof. Preferably the vibrational data represents swallowing activity, is from a sensor positioned on the throat of a patient, and is associated with at least one axis selected from the group consisting of an anterior-posterior axis and a superior-inferior axis. Preferably a processing module operatively connected to the sensor performs the processing of the swallowing segments and the non-swallowing segments of the vibrational data. A device comprising a processing module and a sensor such as a single-axis accelerometer or a dual axis accelerometer can perform one or more steps of the method.

Abstract: A method for motion detection/characterization is provided including the steps of (a) capturing a series of time lapsed images of the ROI, wherein the ROI moves between at least two of such images; (b) generating a motion distribution in relation to the ROI across the series of images; and (c) identifying motion of the ROI based on analysis of the motion distribution. In a further aspect of motion detection/characterization in accordance with the invention, motion is detected/characterized based on calculation of a color distribution for a series of images. A system and computer program for presenting an augmented environment based on the motion detection/characterization is also provided. An interface means based on the motion detection/characterization is also provided.

Abstract: Dual-axis swallowing accelerometry is an emerging tool for the assessment of dysphagia (swallowing difficulties). These signals however can be very noisy as a result of physiological and motion artifacts. A novel scheme for denoising those signals is proposed, i.e., a computationally efficient search for the optimal denoising threshold within a reduced wavelet subspace. To determine a viable subspace, the algorithm relies on the minimum value of the estimated upper bound for the reconstruction error. A numerical analysis of the proposed scheme using synthetic test signals demonstrated that the proposed scheme is computationally more efficient than minimum noiseless description length (MNDL) based de-noising. It also yields smaller reconstruction errors (i.e., higher signal-to-noise (SNR) ratio) than MNDL, SURE and Donoho denoising methods. When applied to dual-axis swallowing accelerometry signals, the proposed scheme improves the SNR values for dry, wet and wet chin tuck swallows.

Abstract: The proposed invention is a method and system for the segmentation of dual-axis accelerometry signals for the purpose of identifying problematic swallowing events. The method and system employ a sensor, a data collection means including an algorithm for analysis of the data. The proposed invention considers the stochastic properties of swallowing signals in both directions, A-P and S-I to extract events associated with swallowing. A segmentation algorithm may be applied to the signals to establish the time duration of swallows and swallows may be classified with respect to gender, body mass index, age or types of swallow.

Abstract: Dual-axis swallowing accelerometry is an emerging tool for the assessment of dysphagia (swallowing difficulties). These signals however can be very noisy as a result of physiological and motion artifacts. A novel scheme for denoising those signals is proposed, i.e. a computationally efficient search for the optimal denoising threshold within a reduced wavelet subspace. To determine a viable subspace, the algorithm relies on the minimum value of the estimated upper bound for the reconstruction error. A numerical analysis of the proposed scheme using synthetic test signals demonstrated that the proposed scheme is computationally more efficient than minimum noiseless description length (MNDL) based de-noising. It also yields smaller reconstruction errors (i.e., higher signal-to-noise (SNR) ratio) than MNDL, SURE and Donoho denoising methods. When applied to dual-axis swallowing accelerometry signals, the proposed scheme improves the SNR values for dry, wet and wet chin tuck swallows.

Abstract: The proposed invention is a method and system for the segmentation of dual-axis accelerometry signals for the purposed of identifying problematic swallowing events. The method and system employ a sensor, a data collection means including an algorithm for the analysis of the data. The proposed invention considers the stochastic properties of swallowing signals in both directions, A-P and S-I to extract events associated with swallowing. A segmentation algorithm may be applied to the signals to establish the time duration of swallows and swallows may be classified with respect to gender, body mass index, age or types of swallow.

Abstract: A method for motion detection/characterization is provided including the steps of (a) capturing a series of time lapsed images of the target, wherein the target moves between at least two of such images; (b) generating a motion distribution in relation to the target across the series of images; and (c) identifying motion of the target based on analysis of the motion distribution. In a further aspect of motion detection/characterization in accordance with the invention, motion is detected/characterized based on calculation of a color distribution for a series of images. A system and computer program for presenting an augmented environment based on the motion detection/characterization is also provided. An interface means based on the motion detection/characterization is also provided.

Abstract: A method for motion detection/characterization is provided including the steps of (a) capturing a series of time lapsed images of the ROI, wherein the ROI moves between at least two of such images; (b) generating a motion distribution in relation to the ROI across the series of images; and (c) identifying motion of the ROI based on analysis of the motion distribution. In a further aspect of motion detection/characterization in accordance with the invention, motion is detected/characterized based on calculation of a color distribution for a series of images. A system and computer program for presenting an augmented environment based on the motion detection/characterization is also provided. An interface means based on the motion detection/characterization is also provided.

Abstract: The proposed invention is a method and system for the segmentation of dual-axis accelerometry signals for the purposed of identifying problematic swallowing events. The method and system employ a sensor, a data collection means including an algorithm for the analysis of the data. The proposed invention considers the stochastic properties of swallowing signals in both directions, A-P and S-I to extract events associated with swallowing. A segmentation algorithm may be applied to the signals to establish the time duration of swallows and swallows may be classified with respect to gender, body mass index, age or types of swallow.

Abstract: A method for motion detection/characterization is provided including the steps of (a) capturing a series of time lapsed images of the target, wherein the target moves between at least two of such images; (b) generating a motion distribution in relation to the target across the series of images; and (c) identifying motion of the target based on analysis of the motion distribution. In a further aspect of motion detection/characterization in accordance with the invention, motion is detected/characterized based on calculation of a color distribution for a series of images. A system and computer program for presenting an augmented environment based on the motion detection/characterization is also provided. An interface means based on the motion detection/characterization is also provided.

Abstract: Vacuum support and rupture disk assembly in which the vacuum support member does not restrict flow through the rupture disk includes a rupture disk having opposite faces defining a plane and a blow-out portion of selected planar dimension; a vacuum support member positionable adjacent a face of the rupture disk and being smaller in planar dimension than the blow-out portion; and a retainer for holding the vacuum support member adjacent the face of the rupture disk and restraining motion of the vacuum support member in all directions except through the rupture disk in such a manner than the entire vacuum support will pass through the blow-out portion if the rupture disk ruptures.