Abstract: Existing multi-wire debugging protocols, such as 4-wire JTAG, 2-wire cJTAG, or ARM SWD, are run through a serial wireless link by providing the debugger and the target device with hardware interfaces that include UARTs and conversion bridges. The debugger interface serializes outgoing control signals and de-serializes returning data. The target interface de-serializes incoming control signals and serializes outgoing data. The actions of the interfaces are transparent to the inner workings of the devices, allowing re-use of existing debugging software. Compression, signal combining, and other optional enhancements increase debugging speed and flexibility while wirelessly accessing target devices that may be too small, too difficult to reach, or too seal-dependent for a wired connection.

Abstract: Existing multi-wire debugging protocols, such as 4-wire JTAG, 2-wire cJTAG, or ARM SWD, are run through a serial wireless link by providing the debugger and the target device with hardware interfaces that include UARTs and conversion bridges. The debugger interface serializes outgoing control signals and de-serializes returning data. The target interface de-serializes incoming control signals and serializes outgoing data. The actions of the interfaces are transparent to the inner workings of the devices, allowing re-use of existing debugging software. Compression, signal combining, and other optional enhancements increase debugging speed and flexibility while wirelessly accessing target devices that may be too small, too difficult to reach, or too seal-dependent for a wired connection.

Abstract: Existing multi-wire debugging protocols, such as 4-wire JTAG, 2-wire cJTAG, or ARM SWD, are run through a serial wireless link by providing the debugger and the target device with hardware interfaces that include UARTs and conversion bridges. The debugger interface serializes outgoing control signals and de-serializes returning data. The target interface de-serializes incoming control signals and serializes outgoing data. The actions of the interfaces are transparent to the inner workings of the devices, allowing re-use of existing debugging software. Compression, signal combining, and other optional enhancements increase debugging speed and flexibility while wirelessly accessing target devices that may be too small, too difficult to reach, or too seal-dependent for a wired connection.

Abstract: Methods and apparatuses for safety enhanced computer-assisted driving. In embodiments, an apparatus for computer-assisted driving may include a neural network to determine a classification for behavior of a driver of a vehicle having the apparatus, based at least in part on data about the vehicle collected in real time, and a current level of stress or drowsiness of the driver determined in real time; and a safety action engine coupled to the neural network to determine a safety related action, based at least in part on the determined driver behavior classification and data related to current traffic or road condition of a route the vehicles is currently traveling on. The safety related action may be performed by an infotainment system or a navigation system of the vehicle to assist the driver in driving the vehicle in a safer manner.

Abstract: Embodiments include apparatuses, methods, and systems including a communication device having a first transceiver to communicate with a first device through a first communication link, and a second transceiver to communicate with a second device through a second communication link. In addition, there may be a third communication link between the first device and the second device. For the communication device, the second transceiver may consume less power for the second communication link than a power the first transceiver consumes to communicate through the first communication link. The communication device may communicate a traffic with the first device via the second device, through the second and third communication links, using the second transceiver. Other embodiments may also be described and claimed.

Abstract: Methods and apparatuses for safety enhanced computer-assisted driving. In embodiments, an apparatus for computer-assisted driving may include a neural network to determine a classification for behavior of a driver of a vehicle having the apparatus, based at least in part on data about the vehicle collected in real time, and a current level of stress or drowsiness of the driver determined in real time; and a safety action engine coupled to the neural network to determine a safety related action, based at least in part on the determined driver behavior classification and data related to current traffic or road condition of a route the vehicles is currently traveling on. The safety related action may be performed by an infotainment system or a navigation system of the vehicle to assist the driver in driving the vehicle in a safer manner.

Abstract: Existing multi-wire debugging protocols, such as 4-wire JTAG, 2-wire cJTAG, or ARM SWD, are run through a serial wireless link by providing the debugger and the target device with hardware interfaces that include UARTs and conversion bridges. The debugger interface serializes outgoing control signals and de-serializes returning data. The target interface de-serializes incoming control signals and serializes outgoing data. The actions of the interfaces are transparent to the inner workings of the devices, allowing re-use of existing debugging software. Compression, signal combining, and other optional enhancements increase debugging speed and flexibility while wirelessly accessing target devices that may be too small, too difficult to reach, or too seal-dependent for a wired connection.

Abstract: The stress detection and management includes a human interface device having a mouse portion to generate cursor control signals and a stress detection portion. The stress detection portion includes a plurality of sensor probes to detect a user's electrical skin response to stress. A sensor is coupled to the plurality of sensor probes to generate a voltage indicative of the skin response to stress. A neural network, coupled to the sensor, generates a stress classification indication based on the voltage indicative of the skin response and pre-training of the neural network with stress indications. The neural network is retrained by comparing the baseline stress classification with the user inputs, using heuristic rules.

Abstract: Various systems and methods for implementing augmented emotion displays are provided herein. A system for displaying emotion embellishments includes a first display device, a processor subsystem, and memory including instructions, which when executed by the processor subsystem cause the processor subsystem to: receive an indication of an emotion being exhibited by a person in a video, the video presented on a first display device; determine an embellishment corresponding to the emotion; and present the embellishment in a location corresponding to the person in the video.

Abstract: A Parkinson's disease (PD) sensor system, including multiple inertial sensors and a heart rate monitor, may be used to detect PD symptoms, including Freezing of Gait (FoG). The PD sensor system may include a wrist-mounted accelerometer and heart rate monitor, and additional inertial sensors at other parts of the patient's body. The FoG detection classifier is implemented as an on-device neural network that will analyze data collected from the inertial sensors and the patient's heart rate to detect FoG events, and simultaneously uses the data to update the FoG event detection specific to the patient's PD symptoms. This self-learning neural network enables a personalized and optimized solution specific to each patient's PD symptoms and disease progression. Once a FoG event is detected, the sensor system may notify a concerned party or may activate an emergency response request.

Abstract: Apparatuses, methods and storage medium associated with enhancing sleep apnea therapy are disclosed herein. In embodiments, an apparatus may comprise one or more light sources to project light onto a user; one or more optical sensors to sense light reflected off the user; and an analyzer coupled with the one or more optical sensors to receive, process and analyze the sensed light data for at least features of heart rate variability signals to determine an apnea condition of the user; wherein the determined apnea condition of the user is used to control an APAP device for the user. Other embodiments may be described and/or claimed.

Abstract: Embodiments include apparatuses, methods, and systems including a communication device having a first transceiver to communicate with a first device through a first communication link, and a second transceiver to communicate with a second device through a second communication link. In addition, there may be a third communication link between the first device and the second device. For the communication device, the second transceiver may consume less power for the second communication link than a power the first transceiver consumes to communicate through the first communication link. The communication device may communicate a traffic with the first device via the second device, through the second and third communication links, using the second transceiver. Other embodiments may also be described and claimed.

Abstract: Existing multi-wire debugging protocols, such as 4-wire JTAG, 2-wire cJTAG, or ARM SWD, are run through a serial wireless link by providing the debugger and the target device with hardware interfaces that include UARTs and conversion bridges. The debugger interface serializes outgoing control signals and de-serializes returning data. The target interface de-serializes incoming control signals and serializes outgoing data. The actions of the interfaces are transparent to the inner workings of the devices, allowing re-use of existing debugging software. Compression, signal combining, and other optional enhancements increase debugging speed and flexibility while wirelessly accessing target devices that may be too small, too difficult to reach, or too seal-dependent for a wired connection.

Abstract: Existing multi-wire debugging protocols, such as 4-wire JTAG, 2-wire cJTAG, or ARM SWD, are run through a serial wireless link by providing the debugger and the target device with hardware interfaces that include UARTs and conversion bridges. The debugger interface serializes outgoing control signals and de-serializes returning data. The target interface de-serializes incoming control signals and serializes outgoing data. The actions of the interfaces are transparent to the inner workings of the devices, allowing re-use of existing debugging software. Compression, signal combining, and other optional enhancements increase debugging speed and flexibility while wirelessly accessing target devices that may be too small, too difficult to reach, or too seal-dependent for a wired connection.

Abstract: A method is provided in one example and includes receiving audio data at a microphone array that includes a plurality of microphones. The microphone array is provisioned at a first endpoint, which includes a camera element configured to capture video data associated with a video session involving the first endpoint and a second endpoint. The method also includes formatting the audio data into a time division multiplex (TDM) stream, and communicating the stream to a port for a subsequent communication over a network and to the second endpoint.

Abstract: A method is provided in one example and includes receiving audio data at a microphone array that includes a plurality of microphones. The microphone array is provisioned at a first endpoint, which includes a camera element configured to capture video data associated with a video session involving the first endpoint and a second endpoint. The method also includes formatting the audio data into a time division multiplex (TDM) stream, and communicating the stream to a port for a subsequent communication over a network and to the second endpoint.

Abstract: A ghost cancellation system for filtering out ghosts in a received video signal including an active filter having a filtering function defined by a first set of coefficients (ak.sub.old) and having a input and a output. A transmitted ghost cancellation reference (GCR) signal is applied to the input of the active filter during a vertical blanking period to generate a filtered GCR signal at the output of the active filter. The filtered GCR signal is compared with a ghostless GCR signal to obtain an error signal, and the filter coefficients are adjusted based on the error signal to obtain a set of new coefficients (ak.sub.new). The active filter includes a feedforward FIR filter and an adder serially connected between the input and the output, a feedback IIR filter and a switch serially connected between the output and-the adder, the feedforward FIR filter and the feedback IIR filter having filtering functions defined by the coefficients.

Abstract: Disclosed is a television ghost cancellation system based on digital filtering. A baseband video signal at the output of the demodulator is lowpass filtered before being digitized at an analog-to-digital converter. The signal is then processed in digital filters to remove the ghosts. The clean digital signal is then passed to a digital-to-analog converter and lowpass filter to become a clean baseband video signal. The digital filters consist of a feedforward section and a feedback section. The coefficients of the digital filters are calculated by digital signal processor, which processes the data stored in First-In-First-Out buffers (FIFOs). The FIFOs are used as outputs, while one FIFO is used as input to the feedback section. The FIFO stores the standard ghost canceler reference (GCR) signal. Switches are controlled by a synchronization separation circuitry. The coefficients of the feedforward section are estimated by processing data stored in the FIFO.