Abstract: Embodiments of the present disclosure disclose reclining seating apparatus with rocking and folding features. The seating apparatus includes a body support portion pivotally connected to a stationary frame, the body support portion including a seat member and a backrest member rotatably coupled with each other, the stationary frame including a first armrest and a second armrest supported by a leg structure. Further, the seating apparatus includes a pair of flexible members configured to adjust and control at least a rocking movement, a reclining movement, or a rocking-reclining movement of the body support portion.

Abstract: A device and method of controlling a device. The device may include a controller for controlling operation of a pumping device to producing a flow of fluid in the pump set, the controller including a processor and a memory, the controller being adapted to store in the memory, syringe size data, the controller configured to execute in the processor a syringe detection program to determine a presence and size of the syringe loaded onto a flow control apparatus.

Abstract: Aspects of the present disclosure relate generally to application ecosystems and, more particularly, to navigational and executional operations in an application ecosystem. In embodiments, a method includes: receiving, by a computing device, a natural language request input by a user to perform a task in an application ecosystem of a plurality of applications; determining, by the computing device, an actionable task from the natural language request to perform in the application ecosystem; generating, by the computing device, a user interface screen to perform the task with input parameters required to perform the task populated in elements of the user interface screen derived from the natural language request; and performing the task with the input parameters required in the application ecosystem of the plurality of applications.

Abstract: An anonymous, decentralized, high speed, open source, data-only, wireless network is deployed in physical space. A server attached to the network generates a Non-Fungible Token (NFT) and associates the NFT with a first network device (e.g., a cellular antennae) before the first network device is deployed in the cellular network. After deployment of the first network device into the cellular network, a second network device (e.g., a network validator) can identify the first network device with information from the NFT. In this way, a digital token can identify a physical piece of hardware for communications within the cellular network.

Abstract: A method and system for contextual heart rate monitoring are disclosed. In a first aspect, the method comprises calculating a heart rate using a detected ECG signal and detecting an activity level. In a second aspect, the system comprises a wireless sensor device coupled to a user via at least one electrode, wherein the wireless sensor device includes a processor and a memory device coupled to the processor, wherein the memory device stores an application which, when executed by the processor, causes the processor to calculate a heart rate using a detected ECG signal and to detect an activity level.

Abstract: A nose cleaning system for personal care and hygiene for the nose includes a nose cleaner having a cleaning head that has a textured surface; a neck that is wider than the cleaning head; a gripping body that is of smaller circumference (or perimeter) than the neck, and ergonomically designed to sit well in the fingers; a handle base; and a cover that is connectable to the neck; and a foaming nose cleanser having a pH of about 6. The foaming nose cleanser includes water (90%); a mix of synthetic detergents (6%); humectants or moisture enhancers (1.5%), salt (1.5%); and additives (1%).

Abstract: A method for designing a logic flow for a user interface is provided. The method comprises receiving from a first task for an automation process file from a user. The automation process file defines a set of system activities. The first task is added to the automation process file and submitted to a machine learning engine, which determines a number of suggested tasks to be performed after the first task. The suggested tasks are based on frequencies with which previous users have used each task after the first task. The suggested tasks are then presented to the user. A second task is received from the user to be performed after the first task. The second task may be selected from the suggested tasks but not necessarily so. The second task is then added to the automation process file.

Abstract: A method for designing a logic flow for a user interface is provided. The method comprises receiving from a first task for an automation process file from a user. The automation process file defines a set of system activities. The first task is added to the automation process file and submitted to a machine learning engine, which determines a number of suggested tasks to be performed after the first task. The suggested tasks are based on frequencies with which previous users have used each task after the first task. The suggested tasks are then presented to the user. A second task is received from the user to be performed after the first task. The second task may be selected from the suggested tasks but not necessarily so. The second task is then added to the automation process file.

Abstract: Various embodiments provide a folding chair. The folding chair includes a frame body having a back, an arm, a front leg and a rear leg frame members. The front and rear leg frame members are configured to support the frame body in an upright position on a ground surface in an unfolded state. Each frame member includes an intermediate section, and a pair of extended sections extending from the intermediate section forming a U-shaped frame member. The frame member also includes a plurality of connecting members moveably coupling the plurality of frame members for allowing the frame body to attain the unfolded state or a folded state. The folding chair also includes a cover member configured to cover the frame body to form at least a seat portion and a backrest portion. The seat portion is supported by the arm frame member and the backrest portion is supported by the back frame member.

Abstract: A method and wireless sensor device for determining step count is disclosed. In one aspect, a method includes receiving sensor data. The method includes detecting if there is activity of the body based on the sensor data. If there is activity, the method also includes classifying the activity and determining step count based on classification of the activity.

Abstract: A method and wireless sensor device for determining body postures and activities. In one aspect, a method includes receiving sensor data. The method also includes detecting and classifying a body transition of a body based on the sensor data. The method also includes detecting if there is activity of the body based on the sensor data. If there is activity, the method also includes classifying the activity. If there is no activity, the method also includes classifying a rest position of the body based on the sensor data and based on a previous body transition.

Abstract: The present invention provides a method of determining the cytotoxic effect of an effector molecule or cell on a target cell presenting a heterologous peptide comprising: (a) incubating said effector molecule or cell with said target cell, wherein said target cell is immobilised on a substrate comprising at least one pair of electrodes; and (b) determining the impedance during and/or after step a) wherein a decrease in impedance is indicative of target cell death.

Abstract: A method and system for calibrating a wireless sensor device are disclosed. In a first aspect, the method comprises determining a vertical calibration vector and determining a rotation matrix using the vertical calibration vector to line up native axes of the wireless sensor device with body axes. In a second aspect, a wireless sensor device comprises a processor and a memory device coupled to the processor, wherein the memory device includes an application that, when executed by the processor, causes the processor to determine a vertical calibration vector and to determine a rotation matrix using the vertical calibration vector to line up native axes of the wireless sensor device with body axes.

Abstract: A method and system for determining psychological acute stress are disclosed. In a first aspect, the method comprises detecting a physiological signal using a wireless sensor device, determining a stress feature using a normalized heart rate and a plurality of heart rate variability (HRV) features, wherein the normalized heart rate and the plurality of heart rate variability features are calculated using the detected physiological signal, and determining a stress level using the stress feature to determine the psychological acute stress. In a second aspect, the system comprises a wireless sensor device that includes a processor and a memory device coupled to the processor, wherein the memory device stores an application which, when executed by the processor, causes the wireless sensor device to carry out the steps of the method.

Abstract: A method and system for measuring respiratory rate are disclosed. In a first aspect, the method comprises measuring at least one respiration signal and filtering the respiration signal using a lowpass filter. The method includes peak-picking the respiration signal to determine the respiratory rate and determining a quality metric of the respiratory rate. In a second aspect, the system comprises a wireless sensor device coupled to a user via at least one electrode, wherein the wireless sensor device includes a processor and a memory device coupled to the processor, wherein the memory device stores an application which, when executed by the processor, causes the processor to carry out the steps of the method.

Abstract: A method and system for contextual heart rate monitoring are disclosed. In a first aspect, the method comprises calculating a heart rate using a detected ECG signal and detecting an activity level. In a second aspect, the system comprises a wireless sensor device coupled to a user via at least one electrode, wherein the wireless sensor device includes a processor and a memory device coupled to the processor, wherein the memory device stores an application which, when executed by the processor, causes the processor to calculate a heart rate using a detected ECG signal and to detect an activity level.

Abstract: A method and system for contextual heart rate monitoring are disclosed. In a first aspect, the method comprises calculating a heart rate using a detected ECG signal and detecting an activity level. In a second aspect, the system comprises a wireless sensor device coupled to a user via at least one electrode, wherein the wireless sensor device includes a processor and a memory device coupled to the processor, wherein the memory device stores an application which, when executed by the processor, causes the processor to calculate a heart rate using a detected ECG signal and to detect an activity level.

Abstract: A method and system for measuring psychological stress disclosed. In a first aspect, the method comprises determining R-R intervals from an electrocardiogram (ECG) to calculate a standard deviation of the R-R intervals (SDNN) and determining a stress feature (SF) using the SDNN. In response to reaching a threshold, the method includes performing adaptation to update a probability mass function (PMF). The method includes determining a stress level (SL) using the SF and the updated PMF to continuously measure the psychological stress. In a second aspect, the system comprises a wireless sensor device coupled to a user via at least one electrode, wherein the wireless sensor device includes a processor and a memory device coupled to the processor, wherein the memory device stores an application which, when executed by the processor, causes the processor to carry out the steps of the method.

Abstract: A method and system for fall detection using machine learning are disclosed. The method comprises detecting at least one signal by a wireless sensor device and calculating a plurality of features from the at least one detected signal. The method includes training a machine learning unit of the wireless sensor device using the features to create a fall classification and a non-fall classification for the fall detection. The system includes a sensor to detect at least one signal, a processor coupled to the sensor, and a memory device coupled to the processor, wherein the memory device includes an application that, when executed by the processor, causes the processor to calculate a plurality of features from the at least one detected signal and to train a machine learning unit of the wireless sensor device using the features to create a fall classification and a non-fall classification for the fall detection.