Abstract: A method for health monitoring is provided including at least one non-invasive wearable device capable of collecting and storing data, and external monitoring devices that displays and analyses the data for accurate monitoring and anomaly detection. The wearable devices are configured to collect low-latency PPG-derived bio signals and can utilize multiple devices for accuracy and continuity. The system may further include a dashboard that analyzes the information as well as displaying basic information such as number of beds (in-use, available), staff-to-patient ratio, etc. The data can be collected and accessed remotely and may be utilized before, during, and/or after a patient is dispatched from a clinical setting.

Abstract: Systems and methods for monitoring the spread of pandemic pneumonia using IOT technology is provided. Sensor data from wearable devices is utilized to determine: a probability of developing complications from a pandemic for an unexposed user using existing indicators of the wearer’s health; the impact of lockdown measures on health; a probability that a user exposed to the pathogen experiences complications; and a probability of various disease stages for the user including normal, asymptomatic, pre-symptomatic, symptomatic, complication development and recovery is provided.

Abstract: A method of detecting coughs using photoplethysmography sensor data is presented. In some embodiments, accelerometry sensor data may also be used in conjunction. A system is presented for the purpose of automatic cough detection, which may also incorporate auxiliary data relevant to the occurrence of coughs. Auxiliary data, may be used to improve cough detection and/or be for contextualization and categorization of detected coughs.

Abstract: The current invention pertains to an apparatus and method for the determination of excess post-exercise oxygen consumption (EPOC) and the estimation of blood lactate levels. While these exercise parameters are traditionally determined using indirect calorimetry and blood sampling, this invention provides a method for the determination of these parameters using heart rate data. A wearable photoplethysmography device for measuring heart rate is included as an exemplary embodiment, however, the method of the current inventions can also be used with heart rate data from any heart rate monitor. In an embodiment of the present invention a supply demand differential equation is used to continuously monitor EPOC in real-time. Furthermore, blood lactate levels can also be estimated as a function of EPOC.

Abstract: A data acquisition device includes measuring instruments to generate physiological and/or psychological data streams. Microprocessors within the acquisition device process the generated data streams into metrics, which feed into stress function algorithms. Algorithm processing may occur either on the device, or metrics may be communicated via wireless communication for external processing on mobile devices and/or cloud-based platforms. The calculated stress functions inform cloud-based computational systems biology-derived models describing the dynamics of hormones and neurotransmitters released in the body in response to stressful stimuli. Stress hormone levels are quantified using these models, and are used in combination to serve as biologically inspired metrics of acute and chronic stress an individual is experiencing.

Abstract: A physiological monitoring system and method for the determination of at least one physiological parameter using a first low energy physiological sensor to produce a first physiological sensor signal and a high energy physiological sensor to produce a second physiological sensor signal. A motion sensor produces a motion reference signal that a mode selector switch uses to select either the first low energy physiological sensor or the second high energy physiological sensor. Alternatively, a motion related embedded component in the second physiological sensor signal is used by the mode selector switch to select in the first low energy sensor or the second high energy sensor.

Abstract: The claimed invention comprises software methods for user continuity and physiological state change assessments through generating biometric profiles of individuals and/or groups of individuals by using physiological input together with biomathematical modeling and machine learning techniques. Intra-individual variation in physiological variables including, but not limited to: heart rate, heart rate variability, pulse waveform and its derivatives, blood pressure, breathing rate, cardiopulmonary coupling, actigraphy and circadian rhythms characteristics, are exploited.

Abstract: The invention comprises methods and systems capable of processing simultaneously measured cardiac and motion signals, selecting from said signals the optimal cardiac and motion signal combination for cross spectral density calculations and, hereafter, itemizing the shared information in terms of the individual constituent frequencies and the effect exerted upon said frequencies by common underlying physiological states. The information is passed through a classifier, where said information is used to quantify the underlying physiological states, exemplified by but not limited to, sleep stage, quality and/or disorders that affect sleep stability. Inferences made by the methods described, for example, can be employed to aid home based sleep analysis and automated screening of patients with sleep disorders.

Abstract: Systems and methods are provided in which data acquisition device detects and captures ambulatory radial arterial blood pressure in a non-invasive and continuous manner through the combined use of tonometry, accelerometry and photoplethysmography, together with the detecting and translating of Mayer waves. Transformed blood pressure data, together with motion and contextual data can be used as input for machine learning algorithms and biomathematical models which can predict the general state of health of an individual. Transformed blood pressure data, together with motion and contextual data, may be communicated via wireless communications to mobile devices and/or cloud based platforms.

Abstract: Computer implemented systems and methods are presented comprising a platform coordinating data flows between data acquisition, data transformation and data delivery nodes, whilst protecting the identities of all entities whose data is being acquired, transformed, stored, and/or delivered. Metadata usage from different data transformation flows enables the platform to facilitate value distribution back to nodes and data subjects that contributed to output, enabling individual companies and/or data subjects subscribed to the platform to assess how and by whom their data is utilized in order to produce specific outputs, with the personal data of all entities being de-identified.

Abstract: The present invention discloses a reflectance type PPG-based physiological sensing system with a close proximity triangulation approach toward robustly measuring several physiological parameters including, but is not limited to, heart rate, breathing rate, blood oxygen saturation and pulse wave velocity.

Abstract: The invention pertains to the establishment, implementation and management of a personalized information system pertinent to a user's general health, wellness and/or sport performance. A set of portable device with calorimetric, metabolic sensing, computing and communication capabilities are used for real-time measurement and display as well as long-term logging of highly accurate information about a user's metabolic state. In an aspect, the invention comprises a portable and hand-held indirect calorimetric device with the capacity to obtain the metabolic parameters of a subject by analyzing the composition of both inspired air and/or expired air of the user.

Abstract: The claimed invention comprises software methods for user continuity and physiological state change assessments through generating biometric profiles of individuals and/or groups of individuals by using physiological input together with biomathematical modeling and machine learning techniques. Intra-individual variation in physiological variables including, but not limited to: heart rate, heart rate variability, pulse waveform and its derivatives, blood pressure, breathing rate, cardiopulmonary coupling, actigraphy and circadian rhythms characteristics, are exploited.

Abstract: Computer implemented systems and methods are presented comprising a platform coordinating data flows between data acquisition, data transformation and data delivery nodes, whilst protecting the identities of all entities whose data is being acquired, transformed, stored, and/or delivered. Metadata usage from different data transformation flows enables the platform to facilitate value distribution back to nodes and data subjects that contributed to output, enabling individual companies and/or data subjects subscribed to the platform to assess how and by whom their data is utilized in order to produce specific outputs, with the personal data of all entities being de-identified.

Abstract: The invention pertains to the establishment, implementation and management of a personalized information system pertinent to a user's general health, wellness and/or sport performance. Disclosed is a system capable of transcutaneous measurement of a subject including at least one light source, at least one light detector, and at least one component for generating or storing at least one value of VC02 or at least one value of V02 from the detected signal. Further, disclosed is a portable device for analyzing the composition of the respired gasses of a subject including at least one air flow conduit through which the subject can inspire or expire air through the body of the device, at least one sampling portal, an oxygen sensor, and at least one flow sensor. A dual-battery system is also provided by which an uninterrupted power supply can be provided for electronic components.

Abstract: The current invention pertains to a method whereby the accuracy of a heart rate prediction gathered from sensor data can be improved during periods when motion corrupts the signal. The model utilized can also be inverted to infer information on the physiological state of a subject, such as real-time energy utilization or physiological load. In addition, this method can also be used to segment the contribution of each energy system, namely the phosphagen system, anaerobic glycolysis and aerobic respiration, to the physiological load experienced by the user. At the core of this approach lies a model describing the dynamic adjustment of human heart rate under varying physiological demands.

Abstract: The claimed invention presents methods for predicting the outcomes of physiological systems in real time using limited data input and computational resources. The claimed invention is comprised of simplified, or abstracted, physiological models, derived from detailed cloud-based computational systems biology models. Abstracted models are capable of utilizing limited data streams, typically obtained from non-invasive data acquisition devices, to accurately estimate, predict and display the outcomes of physiological systems in real time on the device, compared to detailed cloud-based estimations that are computationally demanding and can be used to continuously update abstracted models over time.

Abstract: A data acquisition device includes measuring instruments to generate physiological and/or psychological data streams. Microprocessors within the acquisition device process the generated data streams into metrics, which feed into stress function algorithms. Algorithm processing may occur either on the device, or metrics may be communicated via wireless communication for external processing on mobile devices and/or cloud-based platforms. The calculated stress functions inform cloud-based computational systems biology-derived models describing the dynamics of hormones and neurotransmitters released in the body in response to stressful stimuli. Stress hormone levels are quantified using these models, and are used in combination to serve as biologically inspired metrics of acute and chronic stress an individual is experiencing.

Abstract: Systems and methods are provided in which data acquisition device detects and captures ambulatory radial arterial blood pressure in a non-invasive and continuous manner through the combined use of tonometry, accelerometry and photoplethysmography, together with the detecting and translating of Mayer waves. Transformed blood pressure data, together with motion and contextual data can be used as input for machine learning algorithms and biomathematical models which can predict the general state of health of an individual. Transformed blood pressure data, together with motion and contextual data, may be communicated via wireless communications to mobile devices and/or cloud based platforms.

Abstract: The invention comprises methods and systems capable of processing simultaneously measured cardiac and motion signals, selecting from said signals the optimal cardiac and motion signal combination for cross spectral density calculations and, hereafter, itemizing the shared information in terms of the individual constituent frequencies and the effect exerted upon said frequencies by common underlying physiological states. The information is passed through a classifier, where said information is used to quantify the underlying physiological states, exemplified by but not limited to, sleep stage, quality and/or disorders that affect sleep stability. Inferences made by the methods described, for example, can be employed to aid home based sleep analysis and automated screening of patients with sleep disorders.