Abstract: Contained herein is a system and method for using non-contact diffuse optical skin reflectance method to obtain remote sensing of in-vivo glucose levels in biological tissue or fluids. One embodiment uses an optical, non-contact method capable of measuring glucose levels at a stand-off distance of 0.5 to 2 meters. In this method, the tissue is illuminated with a collimated beam of near-infrared (optical) band of light having a specific band of wavelengths. The diffuse reflectance measured from the tissue/fluid is collected while varying the optical circuit. Using the collected data, an algorithm to unravel the mixed effects of tissue/fluid scattering and absorption is applied to determine the absorption level of the light, which is then associated with a quantitative glucose level.

Abstract: Contained herein is a system and method for using non-contact diffuse optical skin reflectance method to obtain remote sensing of in-vivo glucose levels in biological tissue or fluids. One embodiment uses an optical, non-contact method capable of measuring glucose levels at a stand-off distance of 0.5 to 2 meters. In this method, the tissue is illuminated with a collimated beam of near-infrared (optical) band of light having a specific band of wavelengths. The diffuse reflectance measured from the tissue/fluid is collected while varying the optical circuit. Using the collected data, an algorithm to unravel the mixed effects of tissue/fluid scattering and absorption is applied to determine the absorption level of the light, which is then associated with a quantitative glucose level.

Abstract: There is provided herein a visible light-based speed estimation method ViLDAR. By using the received light intensity of a vehicle's LED headlight, the vehicle speed can be accurately estimated for a wide range of incidence angle. Linear LS method is used in one embodiment of a speed estimation algorithm. The impact of system parameters on speed estimation error and the performance of algorithm for different speed and estimation duration are provided. Some embodiments operate best at a certain distances where the received light intensity (power) reading can provide estimation results with high accuracy, which distances are termed a reliable region of operation. In addition to speed estimation, potential applications of ViLDAR idea are ranging detection and collision avoidance for autonomous vehicles.

Abstract: According to an embodiment there is taught herein a system and method of noncontact human vital signs monitoring using light sensing (also referred to generally herein as visible light sensing (VLS)) that can, in some embodiments, measure in real-time breathing (respiration) and heartbeat rates without body contact. One variation comprises a photo-detector (PD) sensor, which measures signal power level of the reflected light signal from the patient's body and an embedded processing system for the signal processing and filtering on the received light signal. The technology taught herein has the potential to address numerous conditions where the use of contact-based devices may be problematic.

Abstract: There is provided herein a visible light-based speed estimation method ViLDAR. By using the received light intensity of a vehicle's LED headlight, the vehicle speed can be accurately estimated for a wide range of incidence angle. Linear LS method is used in one embodiment of a speed estimation algorithm. The impact of system parameters on speed estimation error and the performance of algorithm for different speed and estimation duration are provided. Some embodiments operate best at a certain distances where the received light intensity (power) reading can provide estimation results with high accuracy, which distances are termed a reliable region of operation. In addition to speed estimation, potential applications of ViLDAR idea are ranging detection and collision avoidance for autonomous vehicles.

Abstract: Aspects described herein relate to adaptive control channel detection in wireless communications. A signal-to-interference-and-noise ratio (SINR) of a signal received by a receiver comprising multiple sub-receivers is measured, wherein the SINR is filtered according to a signal combining technology. Based at least in part on the SINR, it is determined whether to utilize the signal combining technology in combining signals related to a channel received over the multiple sub-receivers.