Introducing a Novel Technique of Detecting Fruits Contaminations Using Terahertz Sensing

This paper mainly presents preliminary results by employing terahertz technology for determining the moisture content (MC) of fruits slices over the course of seven days. In this paper, a novel technique has been presented to determine the transmission and path-loss response of fruits during the loss of moisture content by employing the integrated system of vector network analyzer (VNA) techniques and Swissto12 system over the frequency range from 0.75 THz to 1.1 THz. The results presented in this paper showed that the decreasing MC with the every passing day caused the differences in transmission and path-loss response, which further indicates that the different concentration of substances in fruit emerges a unique absorption characteristic. The application proposed here can be employed for the feasible and non-invasive method of determining the quality control of fruits

Monitoring of atopic dermatitis using leaky coaxial cable

In our daily life, inadvertent scratching may increase the severity of skin diseases (such as atopic dermatitis, etc.). However, people rarely pay attention to this matter, so the known measurement behavior of the movement is also very little. Nevertheless, the behavior and frequency of scratching represent the degree of itching, and the analysis of scratching frequency is helpful to the doctor's clinical dosage. In this paper, a novel system is proposed to monitor the scratching motion of a sleeping human body at night. The core device of the system are just a Leaky coaxial cable (LCX) and a router. Commonly, LCX is used in the blind field or semi blind field in wireless communication. The new idea is that the leaky cable is placed on the bed, then the state information of physical layer of wireless communication channels is acquired to identify the scratching motion and other small body movements in the human sleep process. The results show that it can be used to detect the movement and its duration. Channel state information (CSI) packet is collected by card installed in the computer based on the 802.11n protocol. The characterization of the scratch motion in the collected channel state information is unique, so it can be distinguished from the wireless channel amplitude variation trend

Biometric behavior authentication exploiting propagation characteristics of wireless channel

Massive expansion of wireless body area networks (WBANs) in the field of health monitoring applications has given rise to the generation of huge amount of biomedical data. Ensuring privacy and security of this very personal data serves as a major hurdle in the development of these systems. An effective and energy friendly authentication algorithm is, therefore, a necessary requirement for current WBANs. Conventional authentication algorithms are often implemented on higher levels of the Open System Interconnection model and require advanced software or major hardware upgradation. This paper investigates the implementation of a physical layer security algorithm as an alternative. The algorithm is based on the behavior fingerprint developed using the wireless channel characteristics. The usability of the algorithm is established through experimental results, which show that this authentication method is not only effective, but also very suitable for the energy-, resource-, and interface-limited WBAN medical applications

Towards sparse characterisation of on-body ultra-wideband wireless channels

With the aim of reducing cost and power consumption of the receiving terminal, compressive sensing (CS) framework is applied to on-body ultra-wideband (UWB) channel estimation. It is demonstrated in this Letter that the sparse on-body UWB channel impulse response recovered by the CS framework fits the original sparse channel well; thus, on-body channel estimation can be achieved using low-speed sampling devices

Hand palm local channel characterization for millimeter-wave body-centric applications

The body-centric wireless channel characterization mostly utilizes whole body models. However, localized channels for body parts consistently interacting with the wireless device have their own importance. This paper attempts to characterize the hand palm local channel through experimental measurements at three millimeter-wave frequency bands of 27-28 GHz, 29-30 GHz, and 31-32 GHz. Five human subjects are used in this study. Net body loss is found to be 3dB for different subjects with subject-specific and varying palm shape size is found to be the primary affecting source. The repeatability of the on-body propagation measurements is found to be within 10% of variance

State-of-the-art terahertz sensing for food and water security – a comprehensive review

Background: Recently, there has been a dramatic change in the field of terahertz (THz) technology. The recent advancements in the THz radiation sector considering generation, manipulation and detection have brought revolution in this field, which enable the integration of THz sensing systems into real-world. The THz technology presents detection techniques and various issues, while providing significant opportunities for sensing food and water contamination detection. Scope and approach: Many researchers around the world have exploited the potential of invaluable new applications of THz sensing ranging from surveillance, healthcare and recently for food and water contamination detection. The microbial pollution in water and food is one the crucial issues with regard to the sanitary state for drinking water and daily consumption of food. To address this risk, the detection of microbial contamination is of utmost importance, since the consumption of insanitary or unhygienic food can lead to catastrophic illness. Key findings and conclusions: This paper presents a first-time review of the open literature covering the advances in the THz sensing for microbiological contamination of food and water, in addition to state-of-the-art in network architectures, applications and recent industrial developments. With unique superiority, the THz non-destructive detection technology in food inspection and water contamination detection is emerging as a new area of study. With the great progress, some important challenges and future research directions are presented within the field

Authentication in Millimeter-Wave Body-Centric Networks Through Wireless Channel Characterization

Advent of 5G technologies has ensued in massive growth of body-centric communications (BCCs), especially at millimeter-wave (mm-wave) frequencies. As a result, the portable/handheld terminals are becoming more and more “intelligent” but not without the cost of being less secure. Improved authentication measures need to be explored, as effective identity authentication is the first level of security in these devices. This paper presents a novel keyless authentication method exploiting wireless channel characteristics. Human palm has distinct transmission coefficient (S21) for each of the users and is used for in vivo fingerprint identification in this paper. A detailed channel modeling using data acquisition from real environment and empirical approach is adopted to evaluate the usability of this method. The results show that this method can provide a secure operation for the mm-wave 5G BCCs

Detection and diagnosis of paralysis agitans

Humans’ daily behavior can reflect the main physiological characteristics of neurological diseases. Human gait is a complex behavior produced by the coordination of multiple physiological systems such as the nervous system and the muscular system. It can reflect the physiological state of human health, and its abnormality is an important basis for diagnosing some nervous system diseases. However, many early gait anomalies have not been effectively discovered because of medical costs and people's living customs. This paper proposes an effective, economical, and accurate non-contact cognitive diagnosis system to help early detection and diagnosis of paralysis agitans under daily life conditions. The proposed system extract data from wireless state information obtained from antenna-based data gathering module. Further, we implement data processing and gait classification systems to detect abnormal gait based on the acquired wireless data. In the experiment, the proposed system can detect the state of human gait and carries high classification accuracy up to 96.7 %. The experimental results demonstrate that the proposed technique is feasible and cost-effective for healthcare applications