In this paper, a novel Vision-Based Measurement (VBM) approach is proposed to estimate the contact force and classify materials in a single grasp. This approach is the first event-based tactile sensor which utilizes the recent technology of neuromorphic cameras. This novel approach provides a higher sensitivity, a lower latency, and less computational and power consumption compared to other conventional visionbased techniques. Moreover, Dynamic Vision Sensor (DVS) has a higher dynamic range which increases the sensor sensitivity and performance in poor lighting conditions. Two time-series machine learning methods, namely, Time Delay Neural Network (TDNN) and Gaussian Process (GP) are developed to estimate the contact force in a grasp. A Deep Neural Network (DNN) is proposed to classify the object materials. Forty-eight experiments are conducted for four different materials to validate the proposed methods and compare them against a piezoresistive force sensor measurements. A leave-one-out cross-validation technique is implemented to evaluate and analyze the performance of the proposed machine learning methods. The contact force is successfully estimated with a mean squared error of 0.16 N and 0.17 N for TDNN and GP respectively. Four materials are classified with an average accuracy of 79.17% using unseen experimental data. The results show the applicability of eventbased sensors for grasping applications.

In this paper, a novel approach to detect incipient slip based on the contact area between a transparent silicone medium and different objects using a neuromorphic event-based vision sensor (DAVIS) is proposed. Event-based algorithms are developed to detect incipient slip, slip, stress distribution and object vibration. Thirty-seven experiments were performed on five objects with different sizes, shapes, materials and weights to compare precision and response time of the proposed approach. The proposed approach is validated by using a high speed constitutional camera (1000 FPS). The results indicate that the sensor can detect incipient slippage with an average of 44.1 ms latency in unstructured environment for various objects. It is worth mentioning that the experiments were conducted in an uncontrolled experimental environment, therefore adding high noise levels that affected results significantly. However, eleven of the experiments had a detection latency below 10 ms which shows the capability of this method. The results are very promising and show a high potential of the sensor being used for manipulation applications especially in dynamic environments.

We propose a battery-free temperature monitoring device that can be fitted inside the ear for an accurate body temperature measurement of a subject. The proposed application consists of 2 primary systems: (i) a battery-free temperature sensing Ultra High Frequency Radio Frequency Identification (UHF RFID) sensory tag and (ii), an auxiliary energy harvesting system, which enhances the sensing device's measurement accuracy and precision. The system can record changes in the localized body temperature of authenticated users with an average latency of 501ms. The assembly demonstrated a temperature average accuracy of ± 0.14 °C operating at 866 MHz. The system performance demonstrated high stability and repeatability of reported temperature measurements. The device's dimension is a form factor that can easily fit in a front shirt pocket, with a wire tethered earbud temperature sensor. The system is developed to make sensor measurements without requiring a battery for the device. Measurements are made remotely as users pass by checkpoints installed throughout a building. The device is a cost-effective solution for monitoring body temperature in work environments.

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We present a sub-GHz, low profile Electrically Small Antenna (ESA), designed for UHF RFID miniaturised battery free Implantable Wireless Medical Devices (IWMDs). The custom ESA is a linearly polarised dipole, and its topology leverages a meanderline structure to miniaturise its form factor. Furthermore, the ESA utilises a receded ground plane to improve its gain performance and achieve resonance, at the desired sub-GHz design frequency of 915 MHz. The ESA's dipole characteristics provide an added benefit of 180° bidirectional RF signal propagation. The ESA's design was optimised to integrate the footprint of a UHF RFID sensor chip (SL900A). By integrating the UHF RFID chip on the ESA, a complete wireless battery free sensory medical device, with an integrated antenna, can be realised. The antenna has a formfactor of 12.75×12.25×0.29 mm3. A prototype of the proposed ESA was fabricated and encapsulated in Polydimethylsiloxane (PDMS). Measurements of the prototyped ESA's input reflection coefficient (S11) and farfield gain values, at 915 MHz, were -26.44 dB and -18.88 dBi, respectively and demonstrated significantly better gain and efficiency performance, when compared to peer reviewed work. The ESA can be used as an antenna for various battery-free subcutaneous implants with a connected sensor (e.g. temperature) or actuator (e.g. neurostimulator).