Abstract: The present disclosure provides a description of various methods and systems associated with determining possible presence of Atrial Fibrillation (AF). In one example, a camera of a client device, such as a mobile phone, may acquire a series of images of a body part of a user. A plethysmographic waveform may be generated from the series of images. An autocorrelation function may be calculated from the waveform, and a number of features may be computed from the autocorrelation function. Based on an analysis of the features, a determination may be made about whether the user is experiencing AF. Such determined may be output to a display of the mobile phone for user review.

Abstract: The present disclosure provides a description of various methods and systems associated with determining possible presence of Atrial Fibrillation (AF). In one example, a camera of a client device, such as a mobile phone, may acquire a series of images of a body part of a user. A plethysmographic waveform may be generated from the series of images. An autocorrelation function may be calculated from the waveform, and a number of features may be computed from the autocorrelation function. Based on an analysis of the features, a determination may be made about whether the user is experience AF. Such determined may be output to a display of the mobile phone for user review.

Abstract: The present disclosure provides a description of various methods and systems associated with determining possible presence of Atrial Fibrillation (AF). In one example, a camera of a client device, such as a mobile phone, may acquire a series of images of a body part of a user. A plethysmographic waveform may be generated from the series of images. An autocorrelation function may be calculated from the waveform, and a number of features may be computed from the autocorrelation function. Based on an analysis of the features, a determination may be made about whether the user is experiencing AF. Such determined may be output to a display of the mobile phone for user review.

Abstract: The present disclosure provides a description of various methods and systems associated with determining possible presence of Atrial Fibrillation (AF). In one example, a camera of a client device, such as a mobile phone, may acquire a series of images of a body part of a user. A plethysmographic waveform may be generated from the series of images. An autocorrelation function may be calculated from the waveform, and a number of features may be computed from the autocorrelation function. Based on an analysis of the features, a determination may be made about whether the user is experience AF. Such determined may be output to a display of the mobile phone for user review.

Abstract: In exemplary implementations of this invention, sensor measurements are taken before, during and after an epileptiform seizure of a human. The sensors measure electrodermal activity (EDA) and heart rate variability (HRV) of the human. The EDA and HRV measurements are used to assess sympathetic activity and parasympathetic activity, respectively. More particularly, in the case of HRV measurements, HF power is used to assess parasympathetic innervation of the heart. HF power is the power of the high frequency (e.g. 0.15 to 0.4 Hz) spectral component of the RRI signal. One or more processors analyze the sensor data to calculate the magnitude of a post-ictal autonomic disturbance. Based on that calculated magnitude, the processors assess the severity of the seizure. A wrist-worn sensor may take long-term, continuous EDA and motion measurements. The processors may analyze these measurements to detect the onset of a tonic-clonic seizure.

Abstract: In exemplary implementations of this invention, sensor measurements are taken before, during and after an epileptiform seizure of a human. The sensors measure electrodermal activity (EDA) and heart rate variability (HRV) of the human. The EDA and HRV measurements are used to assess sympathetic activity and parasympathetic activity, respectively. More particularly, in the case of HRV measurements, HF power is used to assess parasympathetic innervation of the heart. HF power is the power of the high frequency (e.g. 0.15 to 0.4 Hz) spectral component of the RRI signal. One or more processors analyze the sensor data to calculate the magnitude of a post-ictal autonomic disturbance. Based on that calculated magnitude, the processors assess the severity of the seizure. A wrist-worn sensor may take long-term, continuous EDA and motion measurements. The processors may analyze these measurements to detect the onset of a tonic-clonic seizure.

Abstract: A washable, wearable biosensor that can gather sensor data, communicate the sensed data by wireless protocols, and permits the analysis of sensed data in real-time as a person goes about their normal lifestyle activities. The biosensor can be worn in multiple positions, can be put on or removed quickly without having to apply or remove gels and adhesives, and provides a snug, comfortable fit to gather data with minimal motion artifacts. The textile, wearable device can support integrated photoplethysmography, skin conductance, motion, and temperature sensors in a small wearable package. The supported sensors may be coupled to utilization devices by channel-sharing wireless protocols to enable the transmission of data from multiple users and multiple sensors (e.g. both sides of body, wrists or hands and feet, or multiple people).

Abstract: Method and system for measuring physiological parameters. The method includes capturing a sequence of images of a human face and identifying the location of the face in a frame of the video and establishing a region of interest including the face. Pixels are separated in the region of interest in a frame into at least two channel values forming raw traces over time. The raw traces are decomposed into at least two independent source signals. At least one of the source signals is processed to obtain a physiological parameter.

Abstract: A washable, wearable biosensor that can gather sensor data, communicate the sensed data by wireless protocols, and permits the analysis of sensed data in real-time as a person goes about their normal lifestyle activities. The biosensor can be worn in multiple positions, can be put on or removed quickly without having to apply or remove gels and adhesives, and provides a snug, comfortable fit to gather data with minimal motion artifacts. The textile, wearable device can support integrated photoplethysmography, skin conductance, motion, and temperature sensors in a small wearable package. The supported sensors may be coupled to utilization devices by channel-sharing wireless protocols to enable the transmission of data from multiple users and multiple sensors (e.g. both sides of body, wrists or hands and feet, or multiple people).