Screen-printed piezoelectric shoe-insole energy harvester using an improved flexible PZT-polymer composites

Maximum power point tracking for a multi-layered piezoelectric heel charger with a levered mechanism toward impact-based energy harvesting

The piezoelectric footstep energy harvester does not always work at its maximum power point when the external load is fixed, as the optimal load changes when the walking excitation alters. Thus, the harvesting efficiency is downgraded largely in real-life scenarios compared to in-lab experiments and theoretical or numerical predictions due to the mismatch between the actual load and the optimal load. To address this issue, the concept of Maximum Power Point Tracking (MPPT) is investigated in this paper and the circuit design is implemented for a multi-layered levered piezoelectric footstep energy harvester (heel charger). The proposed event-driven MPPT circuit interface with a customized buck converter aims to maximize the power gained from daily walking using the heel charger to power a fixed load, such as smart insole or shoes. The MPPT circuit design is conceptually simulated and then tested with the heel charger to further validate if it works at its maximum power point when the frequency of the input excitation alters. Results show that the extracted power from the heel charger connected to a fixed resistance load with MPPT implementation is improved up to 300% compared to the one without MPPT implementation in simulation and up to 180% in the experiment when connected to a fixed load. The difference between simulation and experimental results is due to the optimization of using voltage sources as the heel charger and the control signals (pulse width modulation) from the microcontroller in the simulation.

Comparison between Piezoelectric and Piezoresistive Wearable Gait Monitoring Techniques

Insole plantar stress detection (PSD) techniques play an important role in gait monitoring. Among the various insole PSD methods, piezoelectric- and piezoresistive-based architectures are broadly used in medical scenes. Each year, a growing number of new research outcomes are reported. Hence, a deep understanding of these two kinds of insole PSD sensors and state-of-the-art work would strongly benefit the researchers in this highly interdisciplinary field. In this context, this review article is composed of the following aspects. First, the mechanisms of the two techniques and corresponding comparisons are explained and discussed. Second, advanced materials which could enhance the performance of current piezoelectric and piezoresistive insole prototypes are introduced. Third, suggestions for designing insole PSD prototypes/products for different diseases are offered. Last, the current challenge and potential future trends are provided.

Realization and training of an inverter-based printed neuromorphic computing system

Emerging applications in soft robotics, wearables, smart consumer products or IoT-devices benefit from soft materials, flexible substrates in conjunction with electronic functionality. Due to high production costs and conformity restrictions, rigid silicon technologies do not meet application requirements in these new domains. However, whenever signal processing becomes too comprehensive, silicon technology must be used for the high-performance computing unit. At the same time, designing everything in flexible or printed electronics using conventional digital logic is not feasible yet due to the limitations of printed technologies in terms of performance, power and integration density. We propose to rather use the strengths of neuromorphic computing architectures consisting in their homogeneous topologies, few building blocks and analog signal processing to be mapped to an inkjet-printed hardware architecture. It has remained a challenge to demonstrate non-linear elements besides weighted aggregation. We demonstrate in this work printed hardware building blocks such as inverter-based comprehensive weight representation and resistive crossbars as well as printed transistor-based activation functions. In addition, we present a learning algorithm developed to train the proposed printed NCS architecture based on specific requirements and constraints of the technology.

Footstep Energy Harvesting with the Magnetostrictive Fiber Integrated Shoes

Wearable energy harvesting devices attract attention as the devices provide electrical power without inhibiting user mobility and independence. While the piezoelectric materials integrated shoes have been considered as wearable energy harvesting devices for a long time, they can lose their energy harvesting performance after being used several times due to their brittleness. In this study, we focused on Fe-Co magnetostrictive materials and fabricated Fe-Co magnetostrictive fiber integrated shoes. We revealed that Fe-Co magnetostrictive fiber integrated shoes are capable of generating 1.2 µJ from 1000 steps of usual walking by the Villari (inverse magnetostrictive) effect. It seems that the output energy is dependent on user habit on ambulation, not on their weight. From both a mechanical and functional point of view, Fe-Co magnetostrictive fiber integrated shoes demonstrated stable energy harvesting performance after being used many times. It is likely that Fe-Co magnetostrictive fiber integrated shoes are available as sustainable and wearable energy harvesting devices.