Devices and systems for characterizing a condition of spinal deformities are contemplated. Mobile devices that incorporate inclinometers or accelerometers (e.g., a smart phone) are held securely in a supporting structure that renders it useful to characterize spinal deformities such as scoliosis and/or kyphosis. Supporting structures can include features that secure the mobile device (for example, chamfered surfaces, high friction surfaces, pliant projections, straps, hook and loop enclosures, tensioning devices, detents, etc.) in an upper portion and a lower portion that includes at least one, but preferably two or more rollers, and an interposing centrally placed notch dimensioned to permit the assembled device (supporting structure and mobile device) to span the width of a typical human spinal column. At least one roller includes an encoder (e.g., optical, mechanical, and/or magnetic encoders) that provide data related to their rotation or translation, thereby providing a measure of distance travelled as the device rolls, as well as direction. Such a support device can include additional features, such as additional sensors that are accessible by the mobile device, a centrally placed guide (such as a projected LED laser, illuminated filament, flexible bristle, etc.) that can be used to keep the assembled device in alignment during use, and supplementary battery power for the mobile device.

The embodiments presented herein provide a device comprising a sensor assembly configured to sense physiological signals corresponding to physiological parameters of a user when in contact with the user, and to produce electrical signals representing the sensed physiological signals. The device may also comprise a converter assembly that is electrically connected to the sensor assembly, and is configured to convert the electrical signals to a modulated signal. The device may further comprise a transmitter that transmits the modulated signal wirelessly to a computing device. The device may include a housing that contains the sensor assembly, the converter assembly, and the transmitter.

Systems and methods for medical monitoring devices are provided. Various embodiments include a monitoring device platform. The platform may adhere to a smartphone and house one or more medical monitoring devices to accommodate for one or more health conditions. The medical monitoring devices may be interchangeable and the types of medical monitoring devices on the platform is customizable. The platform may include Bluetooth® functionality and is compatible with smart phones or other smart devices. Medical information collected by the platform is transmitted to the smart phone for viewing by the user. The medical information may be processed by a machine learning engine and can be used to highlight relevant information within an action plan created by a medical professional. Individual medical devices can slide and lock into the platform and may be used while the phone is in use.

A target authentication device includes an electrode to detect an electrical signal associated with a user of the device. The electrical signal represents an authentication code for the device. An authentication receiver module is coupled to the electrode. The module receives the electrical signal from the electrode and determines whether the electrical signal matches a predetermined criterion to authenticate the identity of the user based on the electrical signal. An authentication module is also disclosed. The authentication module includes one electrode to couple an electrical signal associated with a user to a user of a target authentication device, the electrical signal represents an authentication code for the device. An authentication transmission module is coupled to the electrode. The authentication transmission module transmits the electrical signal from the electrode. A method of authenticating the identity of a user of a target authentication device also is disclosed.

A system (100) and a method for analyzing a physiological condition of a user. The system (100) comprises one or more sensors (102a, 102b) to measure one or more parameters including temperature and relative humidity from the user's skin and/or a corresponding temperature and relative humidity from the user's environment via an air gap. A signal representative of the measured parameters is generated. The system (100) also includes at least one transceiver (108) communicably connectable to the sensing unit (102) via one or more communication interfaces, wherein the transceiver (108) is configurable to analyze one or more received signals to initiate one or more events based on the analyzed parameters of the user. The system (100) further includes a processing unit (110) to receive one or more signals from the transceiver (108) and uses artificial intelligence and machine learning techniques to alert users of an impending physiological condition.

A method of calibrating an optical sensor may include acquiring a first characteristic for an external light source through a detector of an optical sensor while an internal light source of the optical sensor is turned off; driving the internal light source; acquiring a second characteristic for the internal light source and the external light source through the detector, based on driving the internal light source; and acquiring a reference characteristic of the internal light source, for calculation of an absorbance of an object, based on the first characteristic and the second characteristic.

An apparatus for measuring bio-information such as blood pressure is provided. The bio-information measuring apparatus includes: a pulse wave sensor configured to measure a pulse wave signal from an object; a fingerprint sensor configured to obtain fingerprint information of the object; and a processor configured to estimate a contact area of the object based on the fingerprint information, and obtain bio-information based on the pulse wave signal and the contact area.

Methods and apparatus provide monitoring of a sleep disordered breathing state of a person such as for screening. One or more sensors may be configured for non-contact active and/or passive sensing. The processor(s) (7304, 7006) may extract respiratory effort signal(s) from one or more motion signals generated by active non-contact sensing with the sensor(s). The processor(s) may extract one or more energy band signals from an acoustic audio signal generated by passive non-contact sensing with the sensor(s). The processor(s) may assess the energy band signal(s) and/or the respiratory efforts signal(s) to generate intensity signal(s) representing sleep disorder breathing modulation. The processor(s) may classify feature(s) derived from the one or more intensity signals to generate measure(s) of sleep disordered breathing. The processor may generate a sleep disordered breathing indicator based on the measure(s) of sleep disordered breathing. Some versions may evaluate sensing signal(s) to generate indication(s) of cough event(s) and/or cough type.

The present invention provides a wellness monitoring system provided with one or more processors and a memory coupled to the one or more processors. The wellness monitoring system includes a first device, a system cloud server, and a second device. The first device is handled by a first person. The first device includes a routine monitoring application configured to collect a set of data associated with the first person. The system cloud server is connected with the first device and the second device through a communication network. The system cloud server collects and stores the set of data collected by the routine monitoring application. The second device is associated with a second person, wherein the second device is configured to review, analyze, and compare, the set of data stored at the system cloud server.

A system to perform neurorehabilitation includes a display that is visible to a user. The system also includes a camera operatively coupled to the display and configured to capture a walking surface upon which the user is walking. The system further includes a processor operatively coupled to the display and to the camera. The processor is configured to project a virtual object onto the walking surface such that the virtual object is visible to the user on the display. The processor is also configured to monitor user movement relative to the virtual object.