Emerging non-invasive microwave and millimeter-wave imaging technologies for food inspection.

The microwave and millimeter-wave (MMW) imaging technology is gaining increasing interest for food inspection. It allows for noninvasive, contactless, and fast scanning capabilities, while being cost-efficient and safe to human. This review paper introduces the fundamentals in the interaction of electromagnetic wave with food materials and the current MMW sensing and imaging systems used for foods.

A Compact Ultra-Wideband Monocone Antenna with Folded Shorting Wires for Vehicle-to-Everything (V2X) Applications.

In this paper, a capacitively-fed, ultra-wideband (UWB), and low-profile monocone antenna is proposed for vehicle-to-everything (V2X) applications. The proposed antenna consists of a monocone design with an inner set of vias. Additionally, an outer ring is added with a small gap from the monocone and shorted with six folded wires of different lengths to extend the operating band.

Lower Body Joint Angle Prediction Using Machine Learning and Applied Biomechanical Inverse Dynamics.

Extreme angles in lower body joints may adversely increase the risk of injury to joints. These injuries are common in the workplace and cause persistent pain and significant financial losses to people and companies. The purpose of this study was to predict lower body joint angles from the ankle to the lumbosacral joint (L5S1) by measuring plantar pressures in shoes.

Microwave imaging for watermelon maturity determination.

Microwave imaging technology is a useful method often applied in medical diagnosis and can be used by the food industry to ensure food safety and quality. For fruit, ripeness is the primary characteristic which determines quality for the consumer. This paper proposes a novel microwave imaging system to determine the ripeness of watermelon as a proof of concept.

Empirical Study on Human Movement Classification Using Insole Footwear Sensor System and Machine Learning.

This paper presents a plantar pressure sensor system (P2S2) integrated in the insoles of shoes to detect thirteen commonly used human movements including walking, stooping left and right, pulling a cart backward, squatting, descending, ascending stairs, running, and falling (front, back, right, left). Six force sensitive resistors (FSR) sensors were positioned on critical pressure points on the insoles to capture the electrical signature of pressure change in the various movements. A total of 34 adult participants were tested with the P2S2.

Ankle Angle Prediction Using a Footwear Pressure Sensor and a Machine Learning Technique.

Ankle injuries may adversely increase the risk of injury to the joints of the lower extremity and can lead to various impairments in workplaces. The purpose of this study was to predict the ankle angles by developing a footwear pressure sensor and utilizing a machine learning technique. The footwear sensor was composed of six FSRs (force sensing resistors), a microcontroller and a Bluetooth LE chipset in a flexible substrate.

Microwave Properties of Coplanar Waveguide-Based PEDOT:PSS Conducting Polymer Line in Ethanol Gas Atmosphere.

This study aims to investigate the microwave properties of coplanar waveguide (CPW)-based poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) conducting polymer line in an ethanol gas atmosphere, with the frequency range of 0.5-2 GHz. For an ethanol-exposed PEDOT:PSS line (test sample), the transmission coefficient () decreased immediately; moreover, the microwave effective conductivity (σ) decreased simultaneously, compared with the ethanol-free PEDOT:PSS line (reference sample).