‪Ex Qualcomm, Intel, Purdue University‬ - ‪‪Cited by 1,237‬‬ - ‪Digital‬ - ‪Mixed Signal VLSI Design‬ - ‪Human Body Communication‬

With a claimed hundredfold power efficiency gain over Bluetooth, Wi-R could bring about the Internet of Touch.

The Wi-R protocol is a non-radiative near-field communication technology that uses Electro-Quasistatic (EQS) fields for communication enabling the body to

Ixana has developed the world’s first high-speed Wi-R silicon chip ready for customer sampling. Wi-R provides smart devices with the ability to securely communicate…

A new wireless technology that uses the human body as a conductor could help usher in a new generation of sleeker VR and AR devices.

Augmenting humans with all-day, real-time, distributed AI on what you see,hear and sense

Electroquasistatics is the branch of electromagnetics involving time-varying electric fields and currents. Get an intro to the theory behind this area of study here.

Since the iPhone 11 announcement, theories have abounded that Apple’s new U1 wireless chip is actually a Decawave Ultra Wideband DW1000. But it turns out the iPhone’s ultra wideband chip is Apple’s own design, and they have some exciting plans for it.

Imec has developed a impulse-radio UWM transmitter IC measuring 0.155mm², with a power consumption of less than 10 milliwatt (mW), fabbed in 28nm CMOS.

At the recent ISSCC conference, imec presented a fast and low-power UWB transmitter chip and a low-power flexible MPU.

Learn more about UWB technology & how it is powering more precise, quick & reliable indoor positioning & asset tracking experiences than ever before.

Thanks to Estimote Indoor Location you can easily map indoor spaces and locate people and objects. Learn more about Estimote Indoor Location in another article. Estimote Automapping is our recent u...

Devices equipped with the Apple-designed Ultra Wideband chip have technology for spatial awareness. Learn which iPhone models and which countries or regions support Ultra Wideband.

Locate and interact with nearby devices using identifiers, distance, and direction.

The Nearby Interaction framework makes it easy to integrate Ultra Wideband (UWB) in your apps and hardware accessories.

Some embodiments include a system, method, and computer program product for managing the Ultra Wideband (UWB) systems, especially when the UWB system is collocated with another wireless system (e.g., WiFi) to transmit and/or receive UWB signals with an occupied bandwidth (OBW) that satisfies a UWB OBW standard (e.g., a UWB OBW>=500 MHz.) In some embodiments a TailBit signal (e.g., a periodic signal at a selected frequency) is added to a UWB packet to generate frequency components at the selected frequency that enables the power spectrum of the TailBit UWB signal to satisfy the UWB OBW standard. In some embodiments an altered code sequence is used to generate an altered spread signal, where the altered code sequence reduces or removes a frequency component peak near DC frequency of the power spectrum of an altered UWB signal, resulting in altered UWB OBW that satisfies the UWB OBW standard.

This invention generally relates to ultra wideband (UWB) communication, and in particular to methods and apparatus for enabling such communicationWC 1 through a building, comprising generating a UWB signal and coupling the UWB signal to at least one electrical conductor of a mains power supply circuit of the building to distribute the UWB signal. This facilitates implementation of a UWB network with reduced interference. AlterWC 1native building wiring systems may be employed such as Cat 5 for computer networking or onWC 1e or two conducters of a telephone cable. The coupling may be direct or contactless such as capacitative coupling.

The article is dicussing the vibration mesurement possibilities and the translation from acceleration to velocity.

Detect anomalies in industrial-machine vibration data using machine learning and deep learning.

ETSI Ultra Wide Band technology page

COPD is a progressive disease that may lead to death if not diagnosed and treated at an early stage. The examination of vital signs such as respiration rate is a promising approach for the detection of COPD. However, simultaneous consideration of the demographic and medical characteristics of patients is very important for better results. The objective of this research is to investigate the capability of UWB radar as a non-invasive approach to discriminate COPD patients from healthy subjects. The non-invasive approach is beneficial in pandemics such as the ongoing COVID-19 pandemic, where a safe distance between people needs to be maintained. The raw data are collected in a real environment (a hospital) non-invasively from a distance of 1.5 m. Respiration data are then extracted from the collected raw data using signal processing techniques. It was observed that the respiration rate of COPD patients alone is not enough for COPD patient detection. However, incorporating additional features such as age, gender, and smoking history with the respiration rate lead to robust performance. Different machine-learning classifiers, including Naïve Bayes, support vector machine, random forest, k nearest neighbor (KNN), Adaboost, and two deep-learning models—a convolutional neural network and a long short-term memory (LSTM) network—were utilized for COPD detection. Experimental results indicate that LSTM outperforms all employed models and obtained 93% accuracy. Performance comparison with existing studies corroborates the superior performance of the proposed approach.