METHOD AND APPARATUS FOR ASSESSMENT OF SLEEP APNEA
First Claim
1. A method for automatically identifying sleep apnea in a subject during sleep, the method comprising:
- continuously collecting load cell signal data from one or more load cells for a duration, the load cells coupled to one or more supports of a bed such that the load cell signal data indicates force exerted against the load cell;
processing the signal data to obtain processed signal data;
extracting features from the processed signal data;
calculating a sleep apnea severity parameter based on the extracted features via a model; and
identifying sleep apnea in the subject based on the sleep apnea severity parameter;
wherein the collecting, processing, extracting, calculating, and identifying are performed by a computing device comprising executable instructions for applying the model to features extracted from the signal data.
0 Assignments
0 Petitions
Accused Products
Abstract
Methods and apparatuses for automatically identifying sleep apnea in a subject based on load cell signal data obtained from load cells coupled with one or more supports of a bed are disclosed. In one example approach, a method comprises continuously collecting load cell signal data from one or more load cells positioned below one or more supports of a bed, processing the signal data to obtain processed signal data, extracting features from the processed signal data, calculating a sleep apnea severity parameter based on the extracted features via a model, and identifying sleep apnea in the subject based on the sleep apnea severity parameter.
9 Citations
20 Claims
-
1. A method for automatically identifying sleep apnea in a subject during sleep, the method comprising:
-
continuously collecting load cell signal data from one or more load cells for a duration, the load cells coupled to one or more supports of a bed such that the load cell signal data indicates force exerted against the load cell; processing the signal data to obtain processed signal data; extracting features from the processed signal data; calculating a sleep apnea severity parameter based on the extracted features via a model; and identifying sleep apnea in the subject based on the sleep apnea severity parameter; wherein the collecting, processing, extracting, calculating, and identifying are performed by a computing device comprising executable instructions for applying the model to features extracted from the signal data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
-
-
12. An apparatus configured to receive information related to sleep apnea in a subject, the apparatus comprising:
-
one or more load cells configured for placement below one or more supports of a bed such that the bed and the one or more bed supports are physically supported by the load cells, the load cells further configured to convert force to an electrical signal indicative of the force; and a computing device coupled to at least one of the one or more load cells, the computing device comprising computer executable instructions for receiving signals from at least one of the one or more load cells, processing the signals to obtain signals representing periods of movement and signals representing periods of stillness, extracting features from the signals representing periods of movement and the signals representing periods of stillness, calculating a sleep apnea severity parameter based on the extracted features via a model, and identifying sleep apnea in the subject based on the sleep apnea severity parameter. - View Dependent Claims (13, 14, 15, 16, 17, 18)
-
-
19. A method for automatically identifying sleep apnea in a subject during sleep, the method comprising:
-
continuously collecting load cell signal data from one or more load cells for a duration, the duration including movement of the subject and stillness of the subject, the load cells being positioned below one or more supports of a bed such that the bed and the one or more bed supports are physically supported by the load cells and the load cell signal data indicates force exerted against the load cell; processing the signal data to obtain processed signal data; identifying movements of the subject throughout the duration based on the processed signal data; determining amplitudes of respiration of the subject throughout the duration based on the processed signal data; identifying disordered breathing events throughout the duration based on the amplitudes of respiration; determining an amount of movement throughout the duration based on the identified movements; calculating a variance in respiration amplitude based on the amplitudes of respiration throughout the duration; calculating a sleep apnea severity parameter based on the number of identified disordered breathing events throughout the duration that meet a predetermined minimum time duration constraint, the amount of movement throughout the duration, and the variance in respiration amplitude; and in response to the sleep apnea severity parameter greater than a threshold, identifying sleep apnea in the subject; wherein the collecting, processing, determining, calculating, and identifying are performed by a computing device. - View Dependent Claims (20)
-
Specification