Chlorophyll a fluorometry has long been used as a method to study phytoplankton in the ocean. In situ fluorometry is used frequently in oceanography to provide depth-resolved estimates of phytoplankton biomass. However, the high price of commercially manufactured in situ fluorometers has made them unavailable to some individuals and institutions. Presented here is an investigation into building an in situ fluorometer using low cost electronics. The goal was to construct an easily reproducible in situ fluorometer from simple and widely available electronic components. The simplicity and modest cost of the sensor makes it valuable to students and professionals alike. Open source sharing of architecture and software will allow students to reconstruct and customize the sensor on a small budget. Research applications that require numerous in situ fluorometers or expendable fluorometers can also benefit from this study. The sensor costs US$150.00 and can be constructed with little to no previous experience. The sensor uses a blue LED to excite chlorophyll a and measures fluorescence using a silicon photodiode. The sensor is controlled by an Arduino microcontroller that also serves as a data logger.
This paper presents a fully differential single-axis accelerometer fabricated using the MetalMUMPs process. The unique structural configuration and common-centriod wiring of the metal electrodes enables a fully differential sensing scheme with robust metal sensing structures. CoventorWare is used in structural and electrical design and simulation of the fully differential accelerometer. The MUMPs foundry fabrication process of the sensor allows for high yield, good process consistency and provides 20 μm structural thickness of the sensing element, which makes the capacitive sensing eligible. In device characterization, surface profile of the fabricated device is measured using a Veeco surface profilometer; and mean and gradient residual stress in the nickel structure are calculated as approximately 94.7 MPa and -5.27 MPa/μm, respectively. Dynamic characterization of the sensor is performed using a vibration shaker with a high-end commercial calibrating accelerometer as reference. The sensitivity of the sensor is measured as 0.52 mV/g prior to off-chip amplification. Temperature dependence of the sensing capacitance is also characterized. A -0.021fF/°C is observed. The findings in the presented work will provide useful information for design of sensors and actuators such as accelerometers, gyroscopes and electrothermal actuators that are to be fabricated using MetalMUMPs technology.
A new gait phase detection system for continuous monitoring based on wireless sensorized insoles is presented. The system can be used in gait analysis mobile applications, and it is designed for real-time demarcation of gait phases. The system employs pressure sensors to assess the force exerted by each foot during walking. A fuzzy rule-based inference algorithm is implemented on a smartphone and used to detect each of the gait phases based on the sensor signals. Additionally, to provide a solution that is insensitive to perturbations caused by non-walking activities, a probabilistic classifier is employed to discriminate walking forward from other low-level activities, such as turning, walking backwards, lateral walking, etc. The combination of these two algorithms constitutes the first approach towards a continuous gait assessment system, by means of the avoidance of non-walking influences.
Rapid localization of injured survivors by rescue teams to prevent death is a major issue. In this paper, a sensor system for human rescue including three different types of sensors, a CO₂ sensor, a thermal camera, and a microphone, is proposed. The performance of this system in detecting living victims under the rubble has been tested in a high-fidelity simulated disaster area. Results show that the CO₂ sensor is useful to effectively reduce the possible concerned area, while the thermal camera can confirm the correct position of the victim. Moreover, it is believed that the use of microphones in connection with other sensors would be of great benefit for the detection of casualties. In this work, an algorithm to recognize voices or suspected human noise under rubble has also been developed and tested.
We present a multifunctional tactile sensor inspired by human hairy skin structure, in which the sensitive hair sensor and the robust skin sensor are integrated into a single device via a pair of Co-based ferromagnetic microwire arrays in a very simple manner. The sensor possesses a self-tunable effective compliance with respect to the magnitude of the stimulus, allowing a wide range of loading force to be measured. The sensor also exhibits some amazing functions, such as air-flow detection, material property characterization, and excellent damage resistance. The novel sensing mechanism and structure provide a new strategy for designing multifunctional tactile sensors and show great potential applications on intelligent robot and sensing in harsh environments.
A new technique for the detection of explosives has been developed based on fluorescence quenching of pyrene on paper-based analytical devices (μPADs). Wax barriers were generated (150 °C, 5 min) using ten different colours. Magenta was found as the most suitable wax colour for the generation of the hydrophobic barriers with a nominal width of 120 μm resulting in fully functioning hydrophobic barriers. One microliter of 0.5 mg mL(-1) pyrene dissolved in an 80 : 20 methanol-water solution was deposited on the hydrophobic circle (5 mm diameter) to produce the active microchip device. Under ultra-violet (UV) illumination, ten different organic explosives were detected using the μPAD, with limits of detection ranging from 100-600 ppm. A prototype of a portable battery operated instrument using a 3 W power UV light-emitting-diode (LED) (365 nm) and a photodiode sensor was also built and evaluated for the successful automatic detection of explosives and potential application for field-based screening.
In underwater locomotion, extracting meaningful information from local flows is as desirable as it is challenging, due to complex fluid-structure interaction. Sensing and motion are tightly interconnected; hydrodynamic signals generated by the external stimuli are modified by the self-generated flow signals. Given that very little is known about self-generated signals, we used onboard pressure sensors to measure the pressure profiles over the head of a fusiform-shape craft while moving forward and backward harmonically. From these measurements we obtained a second-order polynomial model which incorporates the velocity and acceleration of the craft to estimate the surface pressure within the swimming range up to one body length/second (L s-1). The analysis of the model reveals valuable insights into the temporal and spatial changes of the pressure intensity as a function of craft’s velocity. At low swimming velocities (<0.2 L s-1) the pressure signals are more sensitive to the acceleration of the craft than its velocity. However, the inertial effects gradually become less important as the velocity increases. The sensors on the front part of the craft are more sensitive to its movements than the sensors on the sides. With respect to the hydrostatic pressure measured in still water, the pressure detected by the foremost sensor reaches values up to 300 Pa at 1 L s-1 swimming velocity, whereas the pressure difference between the foremost sensor and the next one is less than 50 Pa. Our results suggest that distributed pressure sensing can be used in a bimodal sensing strategy. The first mode detects external hydrodynamic events taking place around the craft, which requires minimal sensitivity to the self-motion of the craft. This can be accomplished by moving slowly with a constant velocity and by analyzing the pressure gradient as opposed to absolute pressure recordings. The second mode monitors the self-motion of the craft. It is shown here that distributed pressure sensing can be used as a speedometer to measure the craft's velocity.
Spectrometry is widely used for the characterization of materials, tissues, and gases, and the need for size and cost scaling is driving the development of mini and microspectrometers. While nanophotonic devices provide narrowband filtering that can be used for spectrometry, their practical application has been hampered by the difficulty of integrating tuning and read-out structures. Here, a nano-opto-electro-mechanical system is presented where the three functionalities of transduction, actuation, and detection are integrated, resulting in a high-resolution spectrometer with a micrometer-scale footprint. The system consists of an electromechanically tunable double-membrane photonic crystal cavity with an integrated quantum dot photodiode. Using this structure, we demonstrate a resonance modulation spectroscopy technique that provides subpicometer wavelength resolution. We show its application in the measurement of narrow gas absorption lines and in the interrogation of fiber Bragg gratings. We also explore its operation as displacement-to-photocurrent transducer, demonstrating optomechanical displacement sensing with integrated photocurrent read-out.
Molecular-electronic transducers (MET) have a high conversion coefficient and low power consumption, and do not require precision mechanical components thus allowing the construction of cost- and power-efficient seismic accelerometers. Whereas the instrumental resolution of a MET accelerometer within the 0.1-100 Hz frequency range surpasses that of the best Micro-Electro Mechanical Systems (MEMS) and even some force-balanced accelerometers, the fundamental inability to register gravity or, in other words, zero frequency acceleration, significantly constrains the further spread of MET-based accelerometers. Ways of obviating this inherent zero frequency insensitivity within MET technology have so far, not been found. This article explores a possible approach to the construction of a hybrid seismic accelerometer combining the superb performance of a MET sensor in the middle and high frequency range with a conventional on chip MEMS accelerometer covering the lower frequencies and gravity. Though the frequency separation of a signal is widely used in various applications, the opposite task, i.e., the combining of two signals with different bandwidths is less common. Based on theoretical research and the analysis of actual sensors' performance, the authors determined optimal parameters for building a hybrid sensor. Description and results for implementation of the hybrid sensor are given in the Experimental section of the article. Completing a MET sensor with a cost-effective MEMS permitted the construction of a low noise DC accelerometer preserving the noise performance of a MET sensing element. The work presented herein may prove useful in designing other combined sensors based on different technologies.
Measuring small normal pressures is essential to accurately evaluate external stimuli in curvilinear and dynamic surfaces such as natural tissues. Usually, sensitive and spatially accurate pressure sensors are achieved through conformal contact with the surface; however, this also makes them sensitive to mechanical deformation (bending). Indeed, when a soft object is pressed by another soft object, the normal pressure cannot be measured independently from the mechanical stress. Here, we show a pressure sensor that measures only the normal pressure, even under extreme bending conditions. To reduce the bending sensitivity, we use composite nanofibres of carbon nanotubes and graphene. Our simulations show that these fibres change their relative alignment to accommodate bending deformation, thus reducing the strain in individual fibres. Pressure sensitivity is maintained down to a bending radius of 80 μm. To test the suitability of our sensor for soft robotics and medical applications, we fabricated an integrated sensor matrix that is only 2 μm thick. We show real-time (response time of ∼20 ms), large-area, normal pressure monitoring under different, complex bending conditions.