Energy harvesting generators are attractive as inexhaustible replacements for batteries in low-power wireless electronic devices and have received increasing research interest in recent years. Ambient motion is one of the main sources of energy for harvesting, and a wide range of motion-powered energy harvesters have been proposed or demonstrated, particularly at the microscale. This paper reviews the principles and state-of-art in motion-driven miniature energy harvesters and discusses trends, suitable applications, and possible future developments.

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Energy Harvesting From Human and Machine Motion for Wireless Electronic Devices

Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application.

https://www.spiedigitallibrary.org/journals/journal-of-biomedical-optics/volume-19/issue-1/010901/Medical-hyperspectral-imaging-a-review/10.1117/1.JBO.19.1.010901.pdf

Medical hyperspectral imaging: a review

Ambient energy harvesting has been in recent years the recurring object of a number of research efforts aimed at providing an autonomous solution to the powering of small-scale electronic mobile devices. Among the different solutions, vibration energy harvesting has played a major role due to the almost universal presence of mechanical vibrations. Here we propose a new method based on the exploitation of the dynamical features of stochastic nonlinear oscillators. Such a method is shown to outperform standard linear oscillators and to overcome some of the most severe limitations of present approaches. We demonstrate the superior performances of this method by applying it to piezoelectric energy harvesting from ambient vibration.

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Nonlinear energy harvesting.

A survey of skin-color modeling and detection methods

2D and 3D face recognition: A survey

Vibration energy harvesting is an attractive technique for potential powering of wireless sensors and low power devices. While the technique can be employed to harvest energy from vibrations and vibrating structures, a general requirement independent of the energy transfer mechanism is that the vibration energy harvesting device operate in resonance at the excitation frequency. Most energy harvesting devices developed to date are single resonance frequency based, and while recent efforts have been made to broaden the frequency range of energy harvesting devices, what is lacking is a robust tunable energy harvesting technique. In this paper, the design and testing of a resonance frequency tunable energy harvesting device using a magnetic force technique is presented. This technique enabled resonance tuning to ±20% of the untuned resonant frequency. In particular, this magnetic-based approach enables either an increase or decrease in the tuned resonant frequency. A piezoelectric cantilever beam with a natural frequency of 26 Hz is used as the energy harvesting cantilever, which is successfully tuned over a frequency range of 22‐32 Hz to enable a continuous power output 240‐280 μW over the entire frequency range tested. A theoretical model using variable damping is presented, whose results agree closely with the experimental results. The magnetic force applied for resonance frequency tuning and its effect on damping and load resistance have been experimentally determined. (Some figures in this article are in colour only in the electronic version)

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A vibration energy harvesting device with bidirectional resonance frequency tunability

Hyperspectral cameras provide useful discriminants for human face recognition that cannot be obtained by other imaging methods. We examine the utility of using near-infrared hyperspectral images for the recognition of faces over a database of 200 subjects. The hyperspectral images were collected using a CCD camera equipped with a liquid crystal tunable filter to provide 31 bands over the near-infrared (0.7 /spl mu/m-1.0 /spl mu/m). Spectral measurements over the near-infrared allow the sensing of subsurface tissue structure which is significantly different from person to person, but relatively stable over time. The local spectral properties of human tissue are nearly invariant to face orientation and expression which allows hyperspectral discriminants to be used for recognition over a large range of poses and expressions. We describe a face recognition algorithm that exploits spectral measurements for multiple facial tissue types. We demonstrate experimentally that this algorithm can be used to recognize faces over time in the presence of changes in facial pose and expression.

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Face recognition in hyperspectral images

Vibration energy harvesting is being pursued as a means to power wireless sensors and ultra-low power autonomous devices. From a design standpoint, matching the electrical damping induced by the energy harvesting mechanism to the mechanical damping in the system is necessary for maximum efficiency. In this work two independent energy harvesting techniques are coupled to provide higher electrical damping within the system. Here the coupled energy harvesting device consists of a primary piezoelectric energy harvesting device to which an electromagnetic component is added to better match the total electrical damping to the mechanical damping in the system. The first coupled device has a resonance frequency of 21.6 Hz and generates a peak power output of ~332 µW, compared to 257 and 244 µW obtained from the optimized, stand-alone piezoelectric and electromagnetic energy harvesting devices, respectively, resulting in a 30% increase in power output. A theoretical model has been developed which closely agrees with the experimental results. A second coupled device, which utilizes the d33 piezoelectric mode, shows a 65% increase in power output in comparison to the corresponding stand-alone, single harvesting mode devices. This work illustrates the design considerations and limitations that one must consider to enhance device performance through the coupling of multiple harvesting mechanisms within a single energy harvesting device.

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A coupled piezoelectric-electromagnetic energy harvesting technique for achieving increased power output through damping matching

Future deployment of wireless sensor networks will ultimately require a self-sustainable local power source for each sensor, and vibration energy harvesting is a promising approach for such applications. A requirement for efficient vibration energy harvesting is to match the device and source frequencies. While techniques to tune the resonance frequency of an energy harvesting device have recently been described, in many applications optimization of such systems will require the energy harvesting device to be able to autonomously tune its resonance frequency. In this work a vibration energy harvesting device with autonomous resonance frequency tunability utilizing a magnetic stiffness technique is presented. Here a piezoelectric cantilever beam array is employed with magnets attached to the free ends of cantilever beams to enable magnetic force resonance frequency tuning. The device is successfully tuned from �27% to +22% of its untuned resonance frequency while outputting a peak power of approximately 1 mW. Since the magnetic force tuning technique is semi-active, energy is only consumed during the tuning process. The developed prototype consumed maximum energies of 3.3 and 3.9 J to tune to the farthest source frequencies with respect to the untuned resonance frequency of the device. The time necessary for this prototype device to harvest the energy expended during its most energy-intensive (largest resonant frequency adjustment) tuning operation is 88 min in a low amplitude 0.1g vibration environment, which could be further optimized using higher efficiency piezoelectric materials and system components. (Some figures in this article are in colour only in the electronic version)

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M. G. Prasad

Papers

A vibration energy harvesting device with bidirectional resonance frequency tunability

Face recognition in hyperspectral images

A coupled piezoelectric-electromagnetic energy harvesting technique for achieving increased power output through damping matching

Towards an autonomous self-tuning vibration energy harvesting device for wireless sensor network applications

A four load method for evaluation of acoustical source impedance in a duct