In this study, a remote caretaking system has been developed by utilizing the plantar pressure measurement feature. This system can be used by medical professionals for patients who require real-time telemonitoring of their gait patterns, activities, and postures. The system consists of a waist belt and accompanying instrumented shoes. The pair of shoes are embedded with tactile sensors, signal conditioning circuitry and Bluetooth communication. The waist belt consists of a Bluetooth module, an accelerometer, GPS module, micro-controller development board and a GPRS module. The complete system has the capability to obtain measurements of the plantar pressures, to detect a predefined posture or activity, calculate gait parameters, find locational information, and to detect falling accidents of the wearer. The system of waist belt and instrumented shoes provides Body Area Network (BAN) features, and establishes a small-scaled network that operates in the peripheral proximity of the human body, using Bluetooth communication. The data acquired by the waist belt is continuously transmitted via a GPRS link to a remote open-source Internet of Things (IOT) platform as data packets which consist of plantar pressure data, identified posture data, and GPS coordinates. The telemonitoring process of the patient is enhanced by the IOT dashboard and the Android application in this system, whereby the real-time data of the posture or activity and locational information can be monitored. To improve convenience, an Android-based mobile application and a web based telemonitoring platform have been implemented, wherein the location, gait information, predefined posture or activity, and falling accidents of the patient can be monitored. Moreover, real-time data is stored in the IOT, with the data stored in the IOT available for post-processing at medical research facilities.

Objective: A Novel Oral Care Simulator was designed and developed to measure and visualise the facial and lingual forces exerted on teeth by the action of tooth brushing, considering the irregular geometry and structural composition of human dentition and the emulation of the realistic biomechanical deflection of the teeth. Method: FEA simulations were carried out on a central incisor under facial loading and an appropriate force sensing mechanism was designed. An anatomically accurate mandibular jaw and 16 teeth were 3D printed, on which 16 force sensing structures were embedded. The signals from the sensors were amplified using a multichannel signal amplifier built using instrumentation amplifiers which were then visualised through a GUI. Results: The developed simulator is capable of indicating the magnitude of a force upto 15 N exerted on to the facial and lingual surfaces of teeth at a frequency of 60 Hz and above and it is capable of alerting the user if the force exceeds a pre-specified threshold. Conclusion: The designed force sensing mechanism considers the irregular geometry and structural composition of human dentition in measuring the facial and lingual forces. It provides a reliable feedback by indicating the force and emulating the realistic biomechanical deflection of teeth. Significance: Nurses who care for the disabled, elderly and sick have explicitly stated the requirement for a simulator to train themselves on brushing the teeth of their subjects as their incorrect technique can cause longterm dental damage, for which a device has not been developed to date.

This paper presents a novel methodology to localise Unmanned Ground Vehicles (UGVs) using Unmanned Aerial Vehicles (UAVs). The UGVs are assumed to be operating in a Global Navigation Satellite System (GNSS)-denied environment. The localisation of the ground vehicles is achieved using UAVs that have full access to the GNSS. The UAVs use range sensors to localise the UGV. One of the major requirements is to use the minimum number of UAVs, which is two UAVs in this paper. Using only two UAVs leads to a significant complication that results an estimation unobservability under certain circumstances. As a solution to the unobservability problem, the main contribution of this paper is to present a methodology to treat the unobservability problem. A Constrained Extended Kalman Filter (CEKF)-based solution, which uses novel kinematics and heuristics-based constraints, is presented. The proposed methodology has been assessed based on the stochastic observability using the Posterior Cramér–Rao Bound (PCRB), and the results demonstrate the successful operation of the proposed localisation method.

Under this research, a novel tactile sensor has been developed using a conductive polymer-based sensing element. The incorporated sensing element is manufactured by polymer press moulding, where the compound is based on silicone rubber and has enhancements by silica and carbon black, with Silane-69 as the coupling agent. Characteristics of the sensing element have been observed using its sensitivity and range, where its results pose an inherent nonlinearity of conductive polymers. For the force scaling purpose, a novel 3D printed cylindrical arch spring structure was developed for this highly customizable tactile sensor by adopting commonly available ABSplus material in 3D printing technology. By considering critical dimensions of the structure, finite element analysis was carried out to achieve nearly optimized results. A special electrical routing arrangement was also designed to reduce the routing complexities. The optimized structure was fabricated using the 3D printing technology. A microcontroller-based signal conditioning circuit was introduced to the system for the purpose of acquiring data. The sensor has been tested up to the maximum load condition using a force indenter. This sensor has a maximum applicable range of 90 N with a maximum structural deflection of 4 mm. The sensor assembly weighs 155 g and the outer dimensions are 85 mm in diameter and 83 mm in height.