Choice of Piezoelectric Element over Accelerometer for an Energy-Autonomous Shoe-Based System

Shoe-based wearable sensor systems are a growing research area in health monitoring, disease diagnosis, rehabilitation, and sports training. These systems—equipped with one or more sensors, either of the same or different types—capture information related to foot movement or pressure maps beneath the foot. This captured information offers an overview of the subject’s overall movement, known as the human gait. Beyond sensing, these systems also provide a platform for hosting ambient energy harvesters. They hold the potential to harvest energy from foot movements and operate related low-power devices sustainably. This article proposes two types of strategies (Strategy 1 and Strategy 2) for an energy-autonomous shoe-based system. Strategy 1 uses an accelerometer as a sensor for gait acquisition, which reflects the classical choice. Strategy 2 uses a piezoelectric element for the same, which opens up a new perspective in its implementation. In both strategies, the piezoelectric elements are used to harvest energy from foot activities and operate the system. The article presents a fair comparison between both strategies in terms of power consumption, accuracy, and the extent to which piezoelectric energy harvesters can contribute to overall power management. Moreover, Strategy 2, which uses piezoelectric elements for simultaneous sensing and energy harvesting, is a power-optimized method for an energy-autonomous shoe system

Development of Piezoelectric Nano- generator with Super-Capacitor

Harvesting mechanical energy from human motion is an attractive approach for obtaining clean and sustainable electric energy to power wearable sensors, which are widely used for health monitoring, activity recognition, gait analysis and so on. This paper studies a piezoelectric energy based device which conserve mechanical energy in shoes originated from human motion. The device is based on a on a pressure based energy generation. Besides, consideration is given to both high performance durability and build with repect to keeping the comfort in mind . The device provides an average output power of 1 mW during a walk at a frequency of roughly 1 Hz., a direct current (DC) power supply is built through integrating the device with a power management circuit

A Review of Piezoelectric Footwear Energy Harvesters: Principles, Methods, and Applications

Over the last couple of decades, numerous piezoelectric footwear energy harvesters (PFEHs) have been reported in the literature. This paper reviews the principles, methods, and applications of PFEH technologies. First, the popular piezoelectric materials used and their properties for PEEHs are summarized. Then, the force interaction with the ground and dynamic energy distribution on the footprint as well as accelerations are analyzed and summarized to provide the baseline, constraints, potential, and limitations for PFEH design. Furthermore, the energy flow from human walking to the usable energy by the PFEHs and the methods to improve the energy conversion efficiency are presented. The energy flow is divided into four processing steps: (i) how to capture mechanical energy into a deformed footwear, (ii) how to transfer the elastic energy from a deformed shoes into piezoelectric material, (iii) how to convert elastic deformation energy of piezoelectric materials to electrical energy in the piezoelectric structure, and (iv) how to deliver the generated electric energy in piezoelectric structure to external resistive loads or electrical circuits. Moreover, the major PFEH structures and working mechanisms on how the PFEHs capture mechanical energy and convert to electrical energy from human walking are summarized. Those piezoelectric structures for capturing mechanical energy from human walking are also reviewed and classified into four categories: flat plate, curved, cantilever, and flextensional structures. The fundamentals of piezoelectric energy harvesters, the configurations and mechanisms of the PFEHs, as well as the generated power, etc., are discussed and compared. The advantages and disadvantages of typical PFEHs are addressed. The power outputs of PFEHs vary in ranging from nanowatts to tens of milliwatts. Finally, applications and future perspectives are summarized and discussed

Wearable with integrated piezoelectric energy harvester for geolocation of people with Alzheimer's

Alzheimer's is a progressive disease that affects memory, causing disorientation in the patient, which causes them to lose themselves, generating anguish in families who have to resort to expensive searches. The objective of this research was to implement a device that can remotely provide the location of the Alzheimer's patient over a long period to relatives for greater security. For this, in this research, a mobile application was developed that receives information from a wearable that applies the internet of things using ong-range wide area technology to show the patient's real-time location and uses piezoelectrics for greater battery autonomy. The real-time location of the person and the radius of the safe zone in the application were obtained as results, the received signal strength indicator value where the signal was excellent or good had a value of -30 to -89 dB between 0 to 400 meters and the battery discharge time was 11 hours and 44 minutes. It was concluded that the application is interactive, that the piezoelectric system increased the autonomy of the wearable, and that the long-range wide area (LoRa) technology allowed monitoring of the patient's location with great precision at 400 meters

Wearable-based human activity recognition: from a healthcare application to a kinetic energy harvesting approach

Wearable technology is changing society by becoming an essential component of daily life. Human activity recognition (HAR) is one of the most prominent research areas where wearable devices play a key role. The first major contribution to the field in this dissertation is a smart physical work- load tracking system that combines wearable-based HAR and heart rate tracking. The proposed system employs a concept from ergonomics, the Frimat’s method, to compute the physical workload from heart rate measurements within a specified time window. This dissertation includes a case of study where tracking of an individual over the course of 20 days corroborates the ability of the system to assess adaptation to an exercise routine. The second and third contributions of this dissertation point to KEH in wearable environments. The second contribution is an energy logger for wrist-worn systems, with the purpose of tracking energy generation in KEH systems during daily activities. Thus, it is possible to determine if the harvested energy is enough to power a conventional wearable device. The proposed system computes the harvested energy using the characteristics of the objective load, which in this case is a battery charger. I carried out experiments with multiple subjects to examine the generation capabilities of a commercial harvester under the conditions of human motion. This study provides insights of the performance and limitations of kinetic harvesters as battery chargers. The third contribution is a KEH-based HAR system using deep learning, data augmentation and transfer learning to outperform existing classification approaches in the KEH domain. The proposed architecture comprises convolutional neural networks (CNN) and long short-term memory networks (LSTM), which has been demonstrated to outperform other architectures found in the literature. Since deep learning classifiers require large amounts of data, and KEH datasets are limited in size, this thesis also includes the proposal of three data augmentation methods to synthesize KEH signals simulating new users. Finally, transfer learning is employed to build a system that maintains performance independent of device location or the subject wearing the device.DoctoradoDoctor en Ingeniería Eléctrica y Electrónic

An investigation on energy harvesting from wrist for smart electronic devices

In this thesis energy harvested using the wrist movement of human arm is discussed. Human arm is constantly being used during our normal routine work, walking running or doing chores. These actions could be helpful in producing electricity. Previously research has been performed on the human body's ability to produce energy. Magnets have been utilized to design a device that harvests the energy using the wrist movement for electronic devices. The magnets were placed inside a 3-D printed tube and coils were wrapped the tube to convert the electromagnetic field into electricity. It can be worn to collect energy all day long. To determine the maximum performance throughout the arm movements, simulations were performed on software called COMSOL. The experiments were carried out by placing this device on the shaker and open circuit voltage was calculated with and without a resistor using an oscilloscope. The open circuit voltage generated at the least frequency of the shaker was 0.24 V and 0.064 V with resistance and without resistance, respectively. Different frequencies were applied to further measure the voltages. As batteries are constantly being needed to be replaced for the wearable electronic devices so, we developed the device which will continuously recharge them. This is a significant step towards future wearable electronics not requiring battery maintenance as it can charge the batteries as the wearer is normally doing their work in their routine.Bu tezde insan kolunun bilek hareketi kullanılarak elde edilen enerji ele alınmıştır. Normal rutin işlerimizde, yürürken, koşarken veya ev işleri yaparken insan kolu sürekli olarak kullanılmaktadır. Bu eylemler elektrik üretiminde yardımcı olabilir. Daha önce insan vücudunun enerji üretme yeteneği üzerine araştırmalar yapılmıştır. Bu çalışmada mıknatıslar, elektronik cihazlar için bilek hareketini kullanarak enerji toplayan bir cihaz tasarlamak için kullanıldı. Mıknatıslar, 3 boyutlu baskılı bir tüpün içine yerleştirildi ve elektromanyetik alanı elektriğe dönüştürmek için tüpe bobinler sarıldı. Bu cihaz gün boyu enerji toplamak için giyilebilir. Kol hareketleri boyunca maksimum performansı belirlemek için COMSOL adı verilen yazılım üzerinde simülasyonlar yapılmıştır. Bu cihaz çalkalayıcı üzerine yerleştirilerek deneyler yapılmış ve osiloskop kullanılarak dirençli ve dirençsiz açık gerilim voltajı hesaplanmıştır. Çalkalayıcının en düşük frekansında üretilen açık devre voltajı dirençli ve dirençsiz durum için sırasıyla 0,24 V ve 0,064 V olmuştur. Voltajları daha fazla ölçmek için farklı frekanslar uygulandı. Giyilebilir elektronik cihazlar için pillerin sürekli olarak değiştirilmesi gerekmektedir. Bu, pilleri şarj edebildiği için pil bakımı gerektirmeyen, geleceğin giyilebilir elektronik cihazlarına doğru önemli bir adımdır çünkü kullanıcı normal olarak rutin işlerini yaparken pilleri şarj edebilir.No sponso

Towards Optimal Kinetic Energy Harvesting for the Batteryless IoT

Traditional Internet of Things (IoT) sensors rely on batteries that need to be replaced or recharged frequently which impedes their pervasive deployment. A promising alternative is to employ energy harvesters that convert the environmental energy into electrical energy. Kinetic Energy Harvesting (KEH) converts the ambient motion/vibration energy into electrical energy to power the IoT sensor nodes. However, most previous works employ KEH without dynamically tracking the optimal operating point of the transducer for maximum power output. In this paper, we systematically analyse the relation between the operating point of the transducer and the corresponding energy yield. To this end, we explore the voltage-current characteristics of the KEH transducer to find its Maximum Power Point (MPP). We show how this operating point can be approximated in a practical energy harvesting circuit. We design two hardware circuit prototypes to evaluate the performance of the proposed mechanism and analyse the harvested energy using a precise load shaker under a wide set of controlled conditions typically found in human-centric applications. We analyse the dynamic current-voltage characteristics and specify the relation between the MPP sampling rate and harvesting efficiency which outlines the need for dynamic MPP tracking. The results show that the proposed energy harvesting mechanism outperforms the conventional method in terms of generated power and offers at least one order of magnitude higher power than the latter

Wearable Energy Harvesting for Charging Portable Electronic Devices by Walking

Wearable energy harvesting technologies will become an everyday part of future portable electronic devices. By generating the energy where the energy is needed and not relying on a main power source to recharge the portable devices battery, wearable energy harvesters will enable future generations to have even more freedoms, travel further, and never run low on battery again. This will reduce the energy consumption of the mains grid and thus in turn reduce CO² emissions generated by this traditional power source making this research important for the whole plant. This research project aims to take another step towards in helping the development of future technologies by investigating novel wearable energy harvesting designs and showing ability to charge current portable electronic devices such as smart phones and tables. This required research into a broad range of topics including, energies from humans, energy conversion mechanisms, the movement of people and the power demands for charging current portable electronic devices. Background research in the human energy levels and how research to date had gone about exacting different energy sources in different ways was the starting point for this research. This leads on to a more detailed look into the exaction methods and optimization of footfall energy harvester designs. Looking into the human gait cycle gave the information required to replicate human footfall motion for use in scientific experiments. From this background research, two bespoke designs of wearable energy harvester have been created. The first novel design showed a promising way of extracting footfall energy and converting it into useable electrical energy producing Watt-Level of power. The second design is an evolution of the first design but expands the extraction method to both feet and relocated the main harvester unit into a backpack worn by the user. The improved design incorporates a novel approach to energy conversion method by introducing a mechanical energy storage system before transduction into electrical energy. This is shown to increased electrical power output from footfall energy, reduced energy consumption of the wearer and is shown to truly be able to charge current portable electronics. The improved design is shown to produce 2.6 Watts average power from normal walking. The experimental set ups, procedures, and their results are shown throughout this thesis. These experimental results are confirmed by using the wearable energy harvesters on a treadmill at the three main walking speeds showing their real-world capabilities. To demonstrate the wearable energy harvester deigns shown in this research project were truly able to charge current portable technologies, endurance testing was also performed. This confirms the harvesters were able to work for longer periods of time. This longer time frame is needed for the charging times of the current portable devices. After researching into wearable energy harvesting from over the last 20 years it was a struggle to compare all the different forms, designs, types and power outputs. It became clear that the existing methods were unable to provide a clear picture of harvester’s scalability, changeability and useability for future design ideas. This is why a new form of comparison was created and is shown to have strong benefits over the existing methods

Simulation and performance analysis of self-powered piezoelectric energy harvesting system for low power applications

Energy harvesting is a process of extracting energy from surrounding environments. The extracted energy is stored in the supply power for various applications like wearable, wireless sensor, and internet of thing (IoT) applications. The electricity generation using conventional approaches is very costly and causes more pollution in the environmental surroundings. In this manuscript, an energy-efficient, self-powered battery-less piezoelectric-based energy harvester (PE-EH) system is modeled using maximum power point tracking (MPPT) module. The MPPT is used to track the optimal voltage generated by the piezoelectric (PE) sensor and stored across the capacitor. The proposed PE system is self-operated without additional microarchitecture to harvest the Power. The experimental simulation results for the overall PE-EH systems are analyzed for different frequency ranges with variable input source vibrations. The optimal voltage storage across the storing capacitor varies from 1.12 to 1.6 V. The PE-EH system can harvest power up to 86 µW without using any voltage source and is suitable for low-power applications. The proposed PE-EH module is compared with the existing similar EH system with better improvement in harvested power

Power Estimation for Wearable Piezoelectric Energy Harvester

The aim of this research work is to estimate the amount of electricity produced to power up wearable devices using a piezoelectric actuator, as an alternative to external power supply. A prototype of the device has been designed to continuously rotate a piezoelectric actuator mounted on a cantilever beam. A MATLAB® simulation was done to predict the amount of power harvested from human kinetic energy. Further simulation was conducted using COMSOL Multiphysics® to model a cantilever beam with piezoelectric layer. With the base excitation and the presence of tip mass at the beam, the natural frequencies and mode shapes have been analyzed to improve the amount of energy harvested. In this work, it was estimated that a maximum amount of power that could be generated is 250 μW with up to 5.5V DC output. The outcome from this research works will aid in optimising the design of the energy harvester. This research work provides optimistic possibility in harvesting sufficient energy required for wearable devices