Low-cost interferometric TDM distributed sensing

In recent years, the number of visually impaired people in Japan has exceeded 300,000 including those with low vision, and accidental falls on the station platform involving them have not been eliminated. Persons having acquired visual impairment make up one third of all cases of blindness in Japan. It is known that they often cannot walk alone with only a white cane or guide dog. The main cause of platform accidents was misidentification of braille blocks. Therefore, it was necessary to develop an auxiliary device for accurately identifying braille blocks that the acquired visually impaired could also use easily. In this research, we developed an automatic identification system for braille blocks using foot pressure data acquired by a multi-channel pressure sensor array. First, we devised a new foot pressure data acquisition device using a multi-channel pressure sensor array. Our proposed device had excellent features such as being light weight, low cost, and easy to extend to multi-channel. Second, in order to accurately identify the braille blocks, the foot pressure data acquired under various conditions was learned by neural network, and identification performance evaluated. As a result of the experiment, the braille blocks could be identified with a high rate of at least 98% accuracy by neural network, with a very simple structure of an input layer (16 neurons), a hidden layer (5 neurons), and an output layer (4 neurons).

Wrist pulse has long been recognized as an important physiological symbol for judging the health status of patients. It is regarded as one of the four diagnosis techniques in traditional Chinese medicine and plays an important role in disease analysis. However, the pulse diagnosis skill is subjective and needs decades of experience to master. To make the pulse diagnosis more objective and easily understood by practitioners, many pulse-taking platforms were invented, but several disadvantages, including the simplicity and insufficiency, limit the applications. This paper proposes a novel wrist pulse system for the pulse diagnosis to overcome the shortcomings in previous pulse platforms. We integrated a pressure sensor with a photoelectric sensor to make a fusion sensor to feel pulse in different approaches and designed the multichannel sensor arrays structure to acquire more pulse information. Finally, pulse analysis algorithm and classification methods are introduced. Experiments on disease classification are carried out to test the system performance with multichannel and different sensor arrays. The results show that the novel system is not only able to distinguish between healthy pulse samples and subjects suffering from diabetes, but also good at obtaining more information than the conventional pulse system with single channel or simplex-type sensor.

The chemical elements of proteins are similar to that of DNA (e.g., C, H, O, and N), and DNA shows different knotted architectures. So we imagine that proteins may show a wealth of highly complex structures, especially when proteins interact with each other. The imagination was proved by synthesizing gold nanoparticles (GNPs) to capture the lifelike protein structures. The optical responses (i.e., color) of as-prepared GNPs are found to be characteristic to a given protein (or heavy metal ion). Based on the “three colors” principle of Thomas Young, we extracted the red, green, and blue (RGB) alterations of as-synthesized GNPs to fabricate multichannel sensor arrays for proteins (or heavy metal ions) discrimination. The designed multichannel sensor arrays demonstrate possibilities in semiquantitative analysis of multiple analytes (e.g., proteins and heavy metal ions). This work is believed to open new opportunities for GNPs-based label-free sensing.

This paper evaluates general purpose processor architecture for efficient implementation of signal processing algorithms to meet the demands of a real-time system. A multi-channel linear sensor array configuration has been considered for underwater surveillance and detection purpose. The paper defines mathematical formulations for calculating the signal processing requirements in terms of data rate and processor loading i.e. FLOPS (floating point operations) that help in selecting an appropriate processor having suitable capacity to carry out the computationally intensive processing algorithms. The paper presents execution times of signal processing algorithms like beam forming and spectral analysis on modern Intel processors that include Core2Quad and Core i7 processors. The results show a considerable reduction in the execution times on Intel Core i7 processor using multithreaded programming approach. An example of DSP architecture has also been discussed to establish the perception of implementing signal processing algorithms on latest Intel processors.

Aiming at promptly and accurately detecting falls and drag-to gaits induced by asynchronous human-robot movement speed during assisted walking, a noncontact interactive approach with generality, compliance and safety is proposed in this paper, and is applied to a wheeled walking aid robot. Firstly, the structure and the functions of the wheeled walking aid robot, including gait rehabilitation robot (GRR) and walking aid robot (WAR) are illustrated, and the characteristic futures of falls and the drag-to gait are shown by experiments. To obtain gait information, a multichannel proximity sensor array is developed, and a two-dimensional gait information detection system is established by combining four proximity sensors groups which are installed in the robot chassis. Additionally, a node-iterative fuzzy Petri net algorithm for abnormal gait recognition is proposed by generating the network trigger mechanism using the fuzzy membership function. It integrates the walking intention direction vector by taking gait deviation, frequency, and torso angle as input parameters of the system. Finally, to improve the compliance of the robot during human-robot interaction, a PID_SC controller is designed by integrating the gait speed compensation, which enables the WAR to track human gait closely. Abnormal gait recognition and assisted walking experiments are carried out respectively. Experimental results show that the proposed algorithm can accurately identify abnormal gaits of different groups of users with different walking habits, and the recognition rate of abnormal gait reaches 91.2%. Results also show that the developed method can guarantee safety in human robot interaction because of user gate follow-up accuracy and compliant movements. The noncontact interactive approach can be applied to robots with similar structure for usage in walking assistance and gait rehabilitation.

Rapid visual authentication of high-temperature Daqu Baijiu using porphyrin signal amplification and smartphone-based cloud machine learning.

A novel multichannel sensor array has been designed using a single, yet multiemissive lanthanide-doped upconversion nanoparticle (UCNP). The energy levels of lanthanide ions gave rise to several emission bands which were exploited as individual sensor elements for the recognition of four important neurotransmitters (NTs): dopamine, norepinephrine, levodopa, and serotonin. At alkaline conditions, the oxidation products of these NTs quenched the fluorescence emissions of UCNPs with different quenching degrees. The resulting fingerprint multichannel emission profiles from NaYF4:Yb/Er/Tm UCNPs allowed the discrimination of NTs with excellent accuracy. The recognition was further verified in artificial cerebrospinal fluid, as a complex biological media. We believe that the designed UCNP-based multichannel sensor array offers innovative insights into the discrimination of various chemical signatures using a single measurement.

Diagnostic methods that use conventional genomic, proteomic, and receptor-based signatures to detect viruses are known. However, they require specialized equipment and personnel for operation, are time consuming and are restricted to the “lock and key” mode of operation. This work reports on the construction of a high-throughput multichannel pattern array sensor platform that can discriminate various viruses rapidly in buffer and in complex matrix and which also can quantitatively discriminate the viruses. The sensor consists of fluorescent semiconductor quantum dots (QDs) capped with four different thiol ligands, namely, 3-mercaptopropionic acid (MPA), L-cysteine (L-cyst), N-acetyl-L-cysteine (NAC) and L-glutathione (GSH) and gold nanoparticles (AuNPs) capped with cationic cetyltrimethylammonium bromide (CTAB). The electrostatic interaction between the negatively charged thiol-capped QDs and the cationic CTAB-AuNP resulted in either a quenched or enhanced fluorescence process. The differing fluorescence process was attributed to the nature of the QDs capping ligand interaction with cationic AuNPs. In the presence of the virus, immobilized AuNPs were displaced from the QDs surface and the QDs fluorescence was restored by localized surface plasmon resonance induced fluorescence intensity. Principal component analysis (PCA), efficiently discriminated the QDs-AuNP array fluorescence intensity data for SARS-CoV 2 spike protein, influenza virus, dengue virus and BK polyomavirus in buffer and in spiked human serum without any overlap. In addition, linear discriminate analysis (LDA) quantitatively discriminated the QDs-AuNP array fluorescence intensity data for different concentrations of SARS-CoV 2 spike protein. The developed QDs-AuNP patterned array sensor is the first of its kind reported for virus discrimination. • Quantum dots (QDs)-gold nanoparticle (AuNP) fluorescence sensor array was fabricated. • Fluorescence intensity array data for various viruses were obtained using the QDs-AuNP nanohybrid. • Fluorescence intensity array data for various viruses was obtained in buffer and human serum. • PCA canonical score plots discriminated the viruses in buffer and human serum. • LDA canonical score plots discriminated discriminate the virus quantitatively.

Stretchable bioelectronics has notably contributed to the advancement of continuous health monitoring and point-of-care type health care. However, microscale nonconformal contact and locally dehydrated interface limit performance, especially in dynamic environments. Therefore, hydrogels can be a promising interfacial material for the stretchable bioelectronics due to their unique advantages including tissue-like softness, water-rich property, and biocompatibility. However, there are still practical challenges in terms of their electrical performance, material homogeneity, and monolithic integration with stretchable devices. Here, we report the synthesis of a homogeneously conductive polyacrylamide hydrogel with an exceptionally low impedance (~21 ohms) and a reasonably high conductivity (~24 S/cm) by incorporating polyaniline-decorated poly(3,4-ethylenedioxythiophene:polystyrene). We also establish robust adhesion (interfacial toughness: ~296.7 J/m2) and reliable integration between the conductive hydrogel and the stretchable device through on-device polymerization as well as covalent and hydrogen bonding. These strategies enable the fabrication of a stretchable multichannel sensor array for the high-quality on-skin impedance and pH measurements under in vitro and in vivo circumstances.

Bioinspired interface-mediated multichannel sensor array for rapid and robust identification of bacteria

We present the laboratory experiments of phase locking of a multi-channel tiled fiber array using a stochastic parallel gradient descent (SPGD) feedback controller demonstrating the compensation effect of the simulating phase-induced distortions based on the model-free optimization of the received signal strength. An all-polarization-maintaining (PM)-fiber optical configuration is used to simplify the free-space transceiver system. The atmospheric aberrations are simulated by a multi-channel integrated optical phase modulator which obtains input control voltages from an array of multi-channel independent sinusoidal signal generators. A similar multi-channel phase modulator which obtains input control voltages from a computer-based SPGD controller is used to compensate the simulating phase distortions. The experimental results show that the constructive interference state is reached through phase locking of the multi-channel tiled fiber array for phase distortions up to 180 hertz for each channel. The update rate of the computer-based SPGD controller is ~16,000 iterations per second. The average compensation bandwidth is about 310 Hz

Studying the temperature field of photovoltaic modules is important for improving their power generation efficiency. To solve the problem of traditional sensors being unsuitable for measuring the spatial temperature field, we designed a real-time detection scheme of the photovoltaic module temperature field based on a fiber Bragg grating (FBG) sensor array. In this scheme, wavelength division multiplexing and space division multiplexing technologies were applied. The multi-channel FBG sensor strings were arranged on the surface and in the near field of the photovoltaic module. Different FBG strings were selected through optical switches, and the wavelength of the FBG string was addressed and demodulated using the tunable laser method and a peak-seeking algorithm. A measurement experiment of the photovoltaic module temperature field was carried out in an outdoor environment. The experimental results showed that the fluctuation law of the photovoltaic module surface and near-field temperature is basically consistent with that of solar radiation power. The temperature of the photovoltaic module decayed from the surface to space. Within 6 mm of the photovoltaic module surface, the temperature sharply dropped, and then the downward trend became flat. The lower the solar radiation power and the higher the wind speed, the faster the temperature decay. This method provides technical support for measuring the temperature field of a photovoltaic module and other heat source equipment.

A fiber sensor array for sub-surface CO2 concentrations measurements was developed for monitoring geologic carbon sequestration sites. The fiber sensor array uses a single temperature tunable distributed feedback (DFB) laser operating with a nominal wavelength of 2.004 μm. Light from this DFB laser is direct to one of the 4 probes via an in-line 1 x 4 fiber optic switch. Each of the 4 probes are buried and allow the sub-surface CO2 to enter the probe through Millipore filters that allow the soil gas to enter the probe but keeps out the soil and water. Light from the DFB laser interacts with the CO2 before it is directed back through the in-line fiber optic switch. The DFB laser is tuned across two CO2 absorption features where a transmission measurement is made allowing the CO2 concentration to be retrieved. The fiber optic switch then directs the light to the next probe where this process is repeated allowing sub-surface CO2 concentration measurements at each of the probes to be made as a function of time. The fiber sensor array was deployed for fifty-eight days beginning June 19, 2012 at the Zero Emission Research Technology (ZERT) field site where sub-surface CO2 concentrations were monitored. Background measurements indicate the fiber sensor array can monitor background levels as low as 1,000 parts per million (ppm). A thirty four day sub-surface release of 0.15 tones CO2/day began on July 10, 2012. The elevated subsurface CO2 concentration was easily detected by each of the four probes with values ranging to over 60,000 ppm, a factor of greater than 6 higher than background measurements. The fiber sensor array was also deploy at the Big Sky Carbon Sequestration Partnership (BSCSP) site in north-central Montana between July 9th and August 7th, 2013 where background measurements were made in a remote sequestration site with minimal infrastructure. The project provided opportunities for two graduate students to participate in research directly related to geologic carbon sequestration. Furthermore, commercialization of the technology developed is being pursued with five different companies via the Department of energy SBIR/STTR program

A multifunction, multichannel remote-reading optical fiber sensor system is presented. The sensor system is based on the principles of frequency modulation continuous wave (FMCW) heterodyne interference, frequency-intensity-division multiplexing. It has the advantages of high measurement accuracy, large measurement range, immunity from electromagnetic interference and temperature influence, noncontact, small probe size, multichannel, and remote reading.© (1991) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

This paper describes recent progress towards the development and qualification of a highly distributed, multi-point, all optical pressure and temperature compensated, fiber optic oxygen sensor (FOxSense™) system for closed-loop monitoring and safety of the oxygen ullage environment inside fuel tanks of military and commercial aircraft. The alloptical FOxSense™ system uses a passive, multi-parameter (O2/T&P) fiber optic sensor probe with no electrical connections leading to the sensors install within the fuel tanks of an aircraft. The all optical sensor consists of an integrated multi-parameter fiber optic sensor probe that integrates a fuel insensitive fluorescence based optical oxygen optrode with built-in temperature and pressure optical optrodes for compensation of temperature and pressure variants induced in the fluorescence response of the oxygen optrode. The distributed (O2/T&P) fiber optic sensors installed in the fuel tanks of the aircraft are connected to the FOxSense optoelectronic system via a fiber optic cable conduit reaching to each fuel tank in the aircraft. A multichannel frequency-domain fiber optic sensor read-out (FOxSense™) system is used to interrogate the optical signal of all three sensors in real-time and to display the fuel tank oxygen environment suitable for aircraft status and alarm applications. Preliminary testing of the all optical fiber optic oxygen sensor have demonstrated the ability to monitor the oxygen environment inside a simulated fuel tank in the range of 0% O2 to 40% O2 concentrations, temperatures from (-) 40°C to (+) 60°C, and altitudes from 0-ft to 40,000-ft.