Electric fencing is commonly used on New Zealand's farms. Modern technology is used in farm management systems to solve old farming problems in a more efficient and simple way. Engineers have researched the use of the electric fence as a communication medium and new technologies based on transmission line theory are used at present to monitor and troubleshoot problems occurring in electric fences. The next stage of the development is to use wireless devices to accomplish those same tasks from remote locations. This project aims to develop a prototype that provides a wireless link between an electric fence and a personal computer in a remote location. This prototype is expected to prove concepts that lead to the future design of useful, marketable products. The project was supported by Gallagher Electronics and is implemented using their existing products where possible.

Current cardiac monitoring devices are rigid, bulky, and integrate poorly with the human skin, obstructing health monitoring for longer periods. With the miniaturization of electronics, soft and stretchable polymer substrate-based cardiac monitoring device is being developed at Mycronic AB to overcome the aforementioned issues and replacing the traditional rigid electronics-based cardiac monitoring devices. Manufacturing of stretchable cardiac monitoring device includes new materials and manufacturing techniques as well as different end-of-life treatments. The sustainability of this kind of stretchable device is often enquired by curious customers and environment enthusiasts. Without a comprehensive scientific study on the environmental performance of this device, it is difficult for the manufacturer to answer such inquiries. Hence, this study aims to carry out a comparative Life Cycle Assessment (LCA) of rigid and stretchable cardiac monitoring devices. The LCA for both the devices was based on ISO 14044:2006 standards. The impact assessment method used was ReCiPe 2016 (Hierarchist). The LCA results showed that the stretchable cardiac monitor had significantly lower impacts than its rigid counterpart. Lower usage of Printed Circuit Board (PCB) in the stretchable device was the main reason for its better environmental performance. The PCB was identified as the major environmental hotspot in both the devices. / Nuvarande hjärtövervakningsanordningar är styva, skrymmande och dåligt integrerade med människans hud och hindrar övervakning under längre perioder. Inom ramen för det europeiska forskingsprojektet SINTEC har Mycronic bidragit till att utveckla en ny design och tillverkningsmetod för en mjuk och töjbar polymersubstratbaserad övervakningsanordning för att övervinna de ovan nämnda hindren med de traditionella alternativ. Tillverkning av töjbar hjärtövervakningsanordning inkluderar nya material och tillverkningstekniker som ger en ökad hållbarhet som ofta efterfrågas av nyfikna kunder och miljöentusiaster. Men utan en omfattande vetenskaplig studie om enhetens miljöprestanda är det dock svårt för tillverkaren att besvara sådana frågor, och därför syftar denna studie till att utföra en jämförande livscykelanalys (LCA) av styva och töjbara hjärtövervakningsanordningar. LCA för båda enheterna baseras på ISO 14044: 2006-standarder. Den konsekvensbedömning som användes var ReCiPe 2016 (Hierarchist). LCA-resultaten visade att den töjbara hjärtmonitorn hade signifikant lägre påverkan än dess styva motsvarighet. Lägre användning av kretskort (PCB) i den töjbara enheten var den främsta anledningen till dess bättre miljöprestanda och just PCB identifierades som den viktigaste miljöhotspoten i båda enheterna.

<p>In recent years, there has been an increase in the popularity of wearable sensors such as electroencephalography (EEG) sensors, electromyography (EMG) sensors, gyroscopes, accelerometers, and photoplethysmography (PPG) sensors. This work is focused on PPG sensors, which are used to measure heart rate in real time. They are currently used in many commercial products such as Fitbit Watch and Muse Headband. Due to their low cost and relative implementation simplicity, they are easy to add to custom-built wearable devices.</p><p><br></p> <p>We built an Arduino-based wearable wrist sensor-kit that consists of a PPG sensor in addition to other low cost commercial biosensors to measure biosignals such as pulse rate, skin temperature, skin conductivity, and hand motion. The purpose of the sensor-kit is to analyze the effects of stress on students in a classroom based on changes in their biometric signals. We noticed some failures in the measured PPG signal, which could negatively affect the accuracy of our analysis. We conjectured that one of the causes of failure is movement. Therefore, in this thesis, we build automatic failure detection methods and use these methods to study the effect of movement on the signal.</p><p><br></p> <p>Using the sensor-kit, PPG signals were collected in two settings. In the first setting, the participants were in a still sitting position. These measured signals were manually labeled and used in signal analysis and method development. In the second setting, the signals were acquired in three different scenarios with increasing levels of activity. These measured signals were used to investigate the effect of movement on the reliability of the PPG sensor. </p><p><br></p> <p>Four types of failure detection methods were developed: Support Vector Machines (SVM), Deep Neural Networks (DNN), K-Nearest Neighbor (K-NN), and Decision Trees. The classification accuracy is evaluated by comparing the resulting Receiver Operating Characteristic (ROC) curves, Area Above the Curve (AAC), as well as the duration of failure and non-failure sequences. The DNN and Decision Tree results are found to be the most promising and seem to have the highest error detection accuracy. </p> <p> </p> <p>The proposed classifiers are also used to assess the reliability of the PPG sensor in the three activity scenarios. Our findings indicate that there is a significant presence of failures in the measured PPG signals at rest, which increases with movement. They also show that it is hard to obtain long sequences of pulses without failure. These findings should be taken into account when designing wearable systems that use heart rate values as input.</p>