A non-invasive, transcutaneous, real-time viral detection device that is configured for self-administration, e.g., at a user's home. In one embodiment, and after positioning the device relative to the human body part (e.g., the user's finger), light sources in the device are activated (excited), and resulting data captured. In particular, a set of Raman spectra are collected from a configured set of emitters and detectors in the device and delivered to a nearby receiver, preferably wirelessly. The receiver filters and de-convolves the Raman spectra producing a data set representative of the constituent elements in the user's tissue of interest. The data set is applied against a statistical classifier, e.g., a neural network that has been trained to recognize and distinguish the absence or presence of viral components, e.g., C-19, or its associated blood-borne acute phase reactants. The classifier outputs an appropriate indicator, preferably in real-time, providing the user with an immediate indication of whether C-19 (or other virus of interest) is present.

A computer-controlled system determines attributes of a frexel, an area of human skin, and applies a modifying agent (RMA) at the pixel level, typically to make the skin appear more youthful and so more attractive. The system scans the frexel, identifies unattractive attributes, and applies the RMA, typically with an inkjet printer. The identified attributes relate to reflectance and may refer to features such as irregular-looking light and dark spots, age-spots, scars, and bruises. Identified attributes may also relate to the surface topology of the skin, for more precisely enhancing surface irregularities such as bumps and wrinkles. Feature mapping may be used, for example to make cheeks appear pinker and cheekbones more prominent. The RMA can be applied in agreement with identified patterns, such as adding red to a red frexel, or in opposition, such as adding green or blue to a red frexel, according to idealized models of attractiveness.

A method 140 of assessing an operator emotional state 131 and sending an alert 144 based on the emotional state 131. The method 140 includes tracking 141 during a time period, using at least one sensor 103, 105, 106, 112, 117, one of an image sensor data, voice data or a biometric parameter of an operator. Determining 142, using a controller 120 that is operatively connected to at least one sensor 103, 105, 106, 112, 117, a probability of a likely emotional state 131 from a list of emotional states 131 of an operator based on one of the image sensor data, voice data or the biometric parameter. Comparing 143, using a processor, the probability of one of the likely emotional states 131 of the operator with a baseline emotional state 131 of the operator. Sending 144, using the controller 120, an alert if most likely emotional state deviates from the baseline emotional state by a predetermined threshold.

The present disclosure relates to systems and methods for positioning a subject. The method may include generating a first image of the subject disposed on a scanning board of an imaging device. The first image may include position information of the subject. The method may further include generating a second image of the subject which includes information associated with one or more organs of the subjects. Additionally, the method may include determining the position of a ROI based on the first image and the second image. The method may further include operating the imaging device to scan a target portion of the subject.

Sensing an environment by confining a monitored live subject in an enclosure, detecting an effect on a coaxial piezoelectric cable resulting from the monitored live subject, wherein the coaxial piezoelectric cable is located at least proximate to the enclosure, and deriving information about a state of the monitored live subject based on the detected effect.

A non-invasive, transcutaneous, real-time viral detection device that is configured for self-administration, e.g., at a user's home. In one embodiment, and after positioning the device relative to the human body part (e.g., the user's finger), light sources in the device are activated (excited), and resulting data captured. In particular, a set of Raman spectra are collected from a configured set of emitters and detectors in the device and delivered to a nearby receiver, preferably wirelessly. The receiver filters and de-convolves the Raman spectra producing a data set representative of the constituent elements in the user's tissue of interest. The data set is applied against a statistical classifier, e.g., a neural network that has been trained to recognize and distinguish the absence or presence of viral components, e.g., C-19, or its associated blood-borne acute phase reactants. The classifier outputs an appropriate indicator, preferably in real-time, providing the user with an immediate indication of whether C-19 (or other virus of interest) is present.

A non-invasive, transcutaneous, real-time viral detection device that is configured for self-administration, e.g., at a user's home. In one embodiment, and after positioning the device relative to the human body part (e.g., the user's finger), light sources in the device are activated (excited), and resulting data captured. In particular, a set of Raman spectra are collected from a configured set of emitters and detectors in the device and delivered to a nearby receiver, preferably wirelessly. The receiver filters and de-convolves the Raman spectra producing a data set representative of the constituent elements in the user's tissue of interest. The data set is applied against a statistical classifier, e.g., a neural network that has been trained to recognize and distinguish the absence or presence of viral components, e.g., C-19, or its associated blood-borne acute phase reactants. The classifier outputs an appropriate indicator, preferably in real-time, providing the user with an immediate indication of whether C-19 (or other virus of interest) is present.

The present disclosure relates to systems and methods for positioning a subject. The method may include generating a first image of the subject disposed on a scanning board of an imaging device. The first image may include position information of the subject. The method may further include generating a second image of the subject which includes information associated with one or more organs of the subjects. Additionally, the method may include determining the position of a ROI based on the first image and the second image. The method may further include operating the imaging device to scan a target portion of the subject.

A sensing system comprising a hand-held sensing device with a vibracoustic sensor module (VSM). The VSM comprises a voice coil component comprising a coil holder supporting wire windings; a magnet component comprising a magnet supported by a frame, a magnet gap configured to receive at least a portion of the voice coil component in a spaced and moveable manner; a connector connecting the voice coil component to the magnet component, the connector being compliant and permitting relative movement of the voice coil component and the magnet component; a diaphragm configured to induce a movement of the voice coil component in the magnet gap responsive to incident acoustic waves; a housing for retaining the vibroacoustic sensor module having a handle end and a sensor end, the sensor end having an opening, the VSM positioned such that at least a portion of the diaphragm extends across the opening.

A non-invasive, transcutaneous, real-time viral detection device that is configured for self-administration, e.g., at a user's home. In one embodiment, and after positioning the device relative to the human body part (e.g., the user's finger), light sources in the device are activated (excited), and resulting data captured. In particular, a set of Raman spectra are collected from a configured set of emitters and detectors in the device and delivered to a nearby receiver, preferably wirelessly. The receiver filters and de-convolves the Raman spectra producing a data set representative of the constituent elements in the user's tissue of interest. The data set is applied against a statistical classifier, e.g., a neural network that has been trained to recognize and distinguish the absence or presence of viral components, e.g., C-19, or its associated blood-borne acute phase reactants. The classifier outputs an appropriate indicator, preferably in real-time, providing the user with an immediate indication of whether C-19 (or other virus of interest) is present.