Small Sensor System Research Articles

Biomimetic Optical-Filter Sensor System for Discrimination of Infrared Chemical Signatures Against a Cold Sky Background

Passive infrared (IR) systems enable rapid detection of chemical vapors but are limited by size, weight, cost, and power. Previously, the authors reported a novel passive sensor that utilizes multiple IR filter/detector combinations to discriminate between different chemical vapors based on their unique IR absorption spectra in the same manner the human eye uses to generate colors. This approach enables a very small, compact, and low-power sensor system with the capability to discriminate between chemical vapors of interest and background chemicals. All previous work showed the capability of this sensor system in discriminating chemical vapors against a hot blackbody in a laboratory environment. Now the authors demonstrate the ability of this sensor system to discriminate between the chemical vapor agent simulant dimethyl methylphosphonate and ethanol against the cold sky in an outdoor environment.

Wireless wearable system based on multifunctional conductive PEG-HEMA hydrogel with anti-freeze, anti-UV, self-healing, and self-adhesive performance for health monitoring

Polymer gels, such as hydrogels, have been widely applied in biomedicine, flexible electronics, and soft robotics. However, due to the complexity of application environments, preparing hydrogels that can maintain comprehensive performance under harsh conditions remains a challenge. Herein, based on polyethylene glycol (PEG) and water as a mixed solvent and using hydroxyethyl methacrylate (HEMA) as a monomer, a conductive dual-network PEG-HEMA hydrogel with anti-freezing, anti-ultraviolet, self-healing, and self-adhesive functions was prepared. The results show that PEG-HEMA hydrogel remained unfrozen even at ‐20°C, with tensile strength and elongation at break of 49.946 KPa and 529.7%, high resolution (able to measure strains as low as 0.2%), good sensitivity and linearity (GF=1.076, R2=0.999), fatigue resistance (over 1000 cycles), and long-term storage capability (over one week). Furthermore, a small wireless wearable strain sensor system was developed by integrating the hydrogel with a microcontroller, which is capable of monitoring various human motion and physiological signals in real time and exhibiting excellent sensing performance. This work provides a straightforward approach for multifunctional hydrogels, and it is expected to attract widespread attention and applications in fields such as electronic skin, human-machine interaction, and human health monitoring.

Tailored Gas Sensors as Rapid Technology to Support the Jams Production

Nowadays, innovation in food technologies is fundamental and consumers are increasingly aware and demanding. To create a final product that is more and more appealing, health and safety guidelines are pushing towards new challenges. It is precisely due to the high quality required by the producers that the aim discussed in this project has been conceived. Until today, the controls on the entire production line have been slowed down by the limitations of the technologies involved, including the high cost of instrumentation for microbiological analysis, the need for qualified personnel to carry them out, the long execution times and the invasiveness of the techniques themselves. This project has, therefore, proposed a user-friendly solution that is minimally invasive, fast and at a lower cost. This system makes use of classical microbiological analysis and, in parallel, use of an innovative electronic-nose small sensor system (S3+), which can be trained to recognize the volatile fingerprint of a specific product and customized for a specific use. The aim of this project was to develop a system that is able to detect the mold contamination on fruit and vegetable jams and marmalades, using a new kind of innovative metal semiconductor gas sensor (MOS) device. The application of this technology has, therefore, made it possible to classify various samples of uncontaminated and contaminated fruit and vegetable preparations. Thanks to the classification implemented by a data-driven algorithm, it has been possible to build an anomaly detector that is able to recognize the occurrence of possible contamination, thus acting as an early alert system in the food chain. All this will occur in less than 1 min once the system is trained, in contrast with classical microbiological or chemical techniques that normally require longer timeframes to obtain a result and involve the use of reagents, increasing the costs.

Volatile Olfactory Profiles of Umbrian Extra Virgin Olive Oils and Their Discrimination through MOX Chemical Sensors.

Extra virgin olive oil (EVOO) is the best vegetable oil worldwide but, at the same time, is one of the product victims of fraud in the agri-food sector, and the differences about quality within the extra-virgin olive oil category are often missed. Several scientific techniques were applied in order to guarantee the authenticity and quality of this EVOO. In the present study, the volatile compounds (VOCs) by gas chromatography–mass spectrometry with solid-phase micro-extraction detection (GC–MS SPME), organoleptic analysis by the official Slow Food panel and the detection by a Small Sensor System (S3) were applied. Ten EVOOs from Umbria, a central Italian region, were selected from the 2021 Slow Food Italian extra virgin olive oil official guide, which includes hundreds of high-quality olive oils. The results demonstrated the possibility to discriminate the ten EVOOs, even if they belong to the same Italian region, by all three techniques. The result of GC–MS SPME detection was comparable at the discrimination level to the organoleptic test with few exceptions, while the S3 was able to better separate some EVOOs, which were not discriminated perfectly by the other two methods. The correlation analysis performed among and between the three methodologies allowed us to identify 388 strong associations with a p value less than 0.05. This study has highlighted how much the mix of VOCs was different even among few and localized EVOOs. The correlation with the sensor detection, which is faster and chipper compared to the other two techniques, elucidated the similarities and discrepancies between the applied methods.

Real Time Monitoring of Wine Vinegar Supply Chain through MOX Sensors.

Vinegar is a fermented product that is appreciated world-wide. It can be obtained from different kinds of matrices. Specifically, it is a solution of acetic acid produced by a two stage fermentation process. The first is an alcoholic fermentation, where the sugars are converted in ethanol and lower metabolites by the yeast action, generally Saccharomyces cerevisiae. This was performed through a technique that is expanding more and more, the so-called “pied de cuve”. The second step is an acetic fermentation where acetic acid bacteria (AAB) action causes the conversion of ethanol into acetic acid. Overall, the aim of this research is to follow wine vinegar production step by step through the volatiloma analysis by metal oxide semiconductor MOX sensors developed by Nano Sensor Systems S.r.l. This work is based on wine vinegar monitored from the grape must to the formed vinegar. The monitoring lasted 4 months and the analyses were carried out with a new generation of Electronic Nose (EN) engineered by Nano Sensor Systems S.r.l., called Small Sensor Systems Plus (S3+), equipped with an array of six gas MOX sensors with different sensing layers each. In particular, real-time monitoring made it possible to follow and to differentiate each step of the vinegar production. The principal component analysis (PCA) method was the statistical multivariate analysis utilized to process the dataset obtained from the sensors. A closer look to PCA graphs affirms how the sensors were able to cluster the production steps in a chronologically correct manner.

A New Kind of Chemical Nanosensors for Discrimination of Espresso Coffee

There are different methods to extract and brew coffee, therefore, coffee processing is an important factor and should be studied in detail. Herein, coffee was brewed by means of a new espresso professional coffee machine, using coffee powder or portioned coffee (capsule). Four different kinds of coffees (Biologico, Dolce, Deciso, Guatemala) were investigated with and without capsules and the goal was to classify the volatiloma of each one by Small Sensor System (S3). The response of the semiconductor metal oxide sensors (MOX) of S3 where recorded, for all 288 replicates and after normalization ∆R/R0 was extracted as a feature. PCA analysis was used to compare and differentiate the same kind of coffee sample with and without a capsule. It could be concluded that the coffee capsules affect the quality, changing on the flavor profile of espresso coffee when extracted different methods confirming the use of s3 device as a rapid and user-friendly tool in the food quality control chain.

A Comprehensive Survey of Visual SLAM Algorithms

Simultaneous localization and mapping (SLAM) techniques are widely researched, since they allow the simultaneous creation of a map and the sensors’ pose estimation in an unknown environment. Visual-based SLAM techniques play a significant role in this field, as they are based on a low-cost and small sensor system, which guarantees those advantages compared to other sensor-based SLAM techniques. The literature presents different approaches and methods to implement visual-based SLAM systems. Among this variety of publications, a beginner in this domain may find problems with identifying and analyzing the main algorithms and selecting the most appropriate one according to his or her project constraints. Therefore, we present the three main visual-based SLAM approaches (visual-only, visual-inertial, and RGB-D SLAM), providing a review of the main algorithms of each approach through diagrams and flowcharts, and highlighting the main advantages and disadvantages of each technique. Furthermore, we propose six criteria that ease the SLAM algorithm’s analysis and consider both the software and hardware levels. In addition, we present some major issues and future directions on visual-SLAM field, and provide a general overview of some of the existing benchmark datasets. This work aims to be the first step for those initiating a SLAM project to have a good perspective of SLAM techniques’ main elements and characteristics.

Internet of Food (IoF), Tailor-Made Metal Oxide Gas Sensors to Support Tea Supply Chain.

Tea is the second most consumed beverage, and its aroma, determined by volatile compounds (VOCs) present in leaves or developed during the processing stages, has a great influence on the final quality. The goal of this study is to determine the volatilome of different types of tea to provide a competitive tool in terms of time and costs to recognize and enhance the quality of the product in the food chain. Analyzed samples are representative of the three major types of tea: black, green, and white. VOCs were studied in parallel with different technologies and methods: gas chromatography coupled with mass spectrometer and solid phase microextraction (SPME-GC-MS) and a device called small sensor system, (S3). S3 is made up of tailor-made metal oxide gas sensors, whose operating principle is based on the variation of sensor resistance based on volatiloma exposure. The data obtained were processed through multivariate statistics, showing the full file of the pre-established aim. From the results obtained, it is understood how supportive an innovative technology can be, remotely controllable supported by machine learning (IoF), aimed in the future at increasing food safety along the entire production chain, as an early warning system for possible microbiological or chemical contamination.

(Invited) How Nanotechnology Can Help the "Zero Hunger" Goal

The elimination of hunger, food insecurity and malnutrition with the aim of creating the basis for a world whose inhabitants feed themselves sufficiently and in a healthy way, in line with their nutritional needs and their food preferences. These are the goals of FAO (Food and Agriculture Organization) for 2030. All researchers are called to make their important contribution.Today there are 842 million hungry people, of whom 200 million are children. From the other European Food Safety Authority (EFSA) declares that 88 million tons of food are thrown away every year, or 173 Kg per person. Data that FAO reports worldwide, 45% of the food produced is thrown away. How nanotechnology can help and contribute to the reduction of food waste, valuable waste if reusable[1]. Nanotechnologies can support the whole process from farm to fork, ensuring that less food is wasted and therefore better used, without compromising the health of the consumer.In this work several studies will be presented in which, Small Sensor System (S3), based on gas sensors with nanomaterials has been used to identify possible contamination of foodstuff and reduce food waste.All the analyzed samples, were prepared in an identical manner for all the techniques used in parallel so as to minimize possible differences. In general, in the food field, techniques that do not go to destroy the sample are preferred, that are fast, and user-friendly, so as to be able to combine as much as possible the real production and food processing.The S3 (Fig.1), consists of a pneumatic part, an electronic part and a chamber with a maximum 10 MOX gas sensors, and an online data acquisition and processing app. Flow, temperature, humidity sensors, and actuators (valves and pumps) are all embedded inside the S3 device. Techniques have been used in parallel to train the sensors, are chemical (GC-MS with SPME) and microbiological (growth media), depending on the specific objective of the application and the nature of the samples [2]. In the case of the reduction of possible microbiological contaminations, the samples will be prepared with known concentrations of bacteria, yeasts or molds, to reproduce real samples.Once acquired and transmitted, data must be analyzed to extract relevant information. Machine learning algorithms are widely used to achieve this purpose, ranging from unsupervised methods (as PCA) to supervised learning (like neural networks, k-NN, SVM, random forest as few examples).Remarkable results have been obtained that demonstrate how the S3 device is able to discriminate in a surprising manner the samples analyzed. The reported results in the food sector concern different types of high applicative interest:- Identification of possible microbiological contaminants such as that from Campylobacter jejuni (Fig.2)[3], - Geographical identification of raw materials (Fig. 3)[4],- Evolution of the shelf-life of a product during the preparation or storage phases,- Environmental monitoring (Fig. 4), such as water purification, air pollution.The food matrices are all complex and constantly evolving, and a device like S3 turns out to bring a considerable advantage to the online control. An advantage that makes it possible to reduce the loss of products at any time, and at the same time increases control enlarging the number of samples analyzed and reducing costs. The aforementioned results demonstrate how nanotechnology and in particular S3 device can contribute to reach the “zero hunger” goal all over the world.[1] S. Vermani, Farm to Fork: IOT for Food Supply Chain, International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8 (2019) 4915 - 4919. DOI: 10.35940/ijitee.L3551.1081219.[2] A.Abbatangelo, E. Núñez-Carmona, V. Sberveglieri, Application of a novel S3 nanowire gas sensor device in parallel with GC-MS for the identification of Parmigiano Reggiano from US and European competitors, J. Food Eng. 236 (2018) 36–43.doi:10.3390/s18051617.[3] E. Núñez-Carmona, M. Abbatangelo,, V. Sberveglieri, Innovative Sensor Approach to Follow Campylobacter jejuni Development, Biosensors, 9 (1) (2019) Article number bios9010008 DOI: 10.3390/bios9010008[4] M. Abbatangelo, E. Núñez-Carmona, G. Duina, V. Sberveglieri, V., Multidisciplinary approach to characterizing the fingerprint of Italian EVoO, Molecules, 24 (8) (2019), DOI: 10.3390/molecules24081457. Figure 1

(Invited) How Nanotechnology Can Help the "Zero Hunger" Goal?

The elimination of hunger, food insecurity and malnutrition with the aim of creating the basis for a world whose inhabitants feed themselves sufficiently and in a healthy way, in line with their nutritional needs and their food preferences. These are the goals of FAO (Food and Agriculture Organization) for 2030. All researchers are called to make their important contribution.Today there are 842 million hungry people, of whom 200 million are children. From the other European Food Safety Authority (EFSA) declares that 88 million tons of food are thrown away every year, or 173 Kg per person. Data that FAO reports worldwide, 45% of the food produced is thrown away. How nanotechnology can help and contribute to the reduction of food waste, valuable waste if reusable[1]. Nanotechnologies can support the whole process from farm to fork, ensuring that less food is wasted and therefore better used, without compromising the health of the consumer.In this work several studies will be presented in which, Small Sensor System (S3), based on gas sensors with nanomaterials has been used to identify possible contamination of foodstuff and reduce food waste.All the analyzed samples, were prepared in an identical manner for all the techniques used in parallel so as to minimize possible differences. In general, in the food field, techniques that do not go to destroy the sample are preferred, that are fast, and user-friendly, so as to be able to combine as much as possible the real production and food processing.The S3 (Fig.1), consists of a pneumatic part, an electronic part and a chamber with a maximum 10 MOX gas sensors, and an online data acquisition and processing app. Flow, temperature, humidity sensors, and actuators (valves and pumps) are all embedded inside the S3 device. Techniques have been used in parallel to train the sensors, are chemical (GC-MS with SPME) and microbiological (growth media), depending on the specific objective of the application and the nature of the samples [2]. In the case of the reduction of possible microbiological contaminations, the samples will be prepared with known concentrations of bacteria, yeasts or molds, to reproduce real samples.Once acquired and transmitted, data must be analyzed to extract relevant information. Machine learning algorithms are widely used to achieve this purpose, ranging from unsupervised methods (as PCA) to supervised learning (like neural networks, k-NN, SVM, random forest as few examples).Remarkable results have been obtained that demonstrate how the S3 device is able to discriminate in a surprising manner the samples analyzed. The reported results in the food sector concern different types of high applicative interest:- Identification of possible microbiological contaminants such as that from Campylobacter jejuni (Fig.2)[3],- Geographical identification of raw materials (Fig. 3)[4],- Evolution of the shelf-life of a product during the preparation or storage phases,- Environmental monitoring (Fig. 4), such as water purification, air pollution.The food matrices are all complex and constantly evolving, and a device like S3 turns out to bring a considerable advantage to the online control. An advantage that makes it possible to reduce the loss of products at any time, and at the same time increases control enlarging the number of samples analyzed and reducing costs. The aforementioned results demonstrate how nanotechnology and in particular S3 device can contribute to reach the “zero hunger” goal all over the world.

Nanomaterial Gas Sensors for Online Monitoring System of Fruit Jams.

Jams are appreciated worldwide and have become a growing market, due to the greater attention paid by consumers for healthy food. The selected products for this study represent a segment of the European market that addresses natural products without added sucrose or with a low content of natural sugars. This study aims to identify volatile organic compounds (VOCs) that characterize three flavors of fruit and five recipes using gas chromatography–mass spectrometry (GC–MS) and solid-phase micro-extraction (SPME) analysis. Furthermore, an innovative device, a small sensor system (S3), based on gas sensors with nanomaterials has been used; it may be particularly advantageous in the production line. Results obtained with linear discriminant analysis (LDA) show that S3 can distinguish among the different recipes thanks to the differences in the VOCs that are present in the specimens, as evidenced by the GC–MS analysis. Finally, this study highlights how the thermal processes for obtaining the jam do not alter the natural properties of the fruit.

Effective Low Leakage 6T and 8T FinFET SRAMs: Using Cells With Reverse-Biased FinFETs, Near-Threshold Operation, and Power Gating

Power gating is commonly used to reduce leakage current in SRAM memories; leakage current has a large impact on SRAM energy consumption. We first focus on power gating FinFET SRAMs and then evaluate three techniques to reduce the leakage power and energy-delay product (EDP) of six- and eight-transistor (6T, 8T) FinFET SRAM cells. We compare the EDP savings obtained using: 1) power gating FinFETs; 2) near-threshold operation at $V_{\mathrm{ DD}}=0.6$ V instead of the nominal $V_{\mathrm{ DD}}=1$ V; and 3) alternative SRAM cells with shorted gate (SG) and low power (LP) configured FinFETs; LP-configuration reverse-biases a FinFET’s back gate and reduces leakage current by up to 97%. SRAM cells with higher leakage benefit the most from power gating since they see the largest reductions in leakage current. Sharing power gating transistors among multiple SRAM cells can lead to more leakage current savings, but causes slower read and write speeds which can diminish their effectiveness. Alternative SRAM cells with lower leakage benefit the most from near-threshold operation to further reduce leakage current. Near-threshold operation and/or power gating reduces the 6T SG FinFET SRAM scheme’s EDP slightly more than using the 8T SG FinFET SRAM scheme, but using an LP 8T SRAM scheme, such as LP_INV1.2, with near-threshold operation is more effective than power gating and provides the largest reductions in EDP. The design techniques recommended by this brief can enable longer battery life for small sensor systems and thus greater reliability for Internet-of-Things (IoT) devices.

A Fully Integrated Counter Flow Energy Reservoir for Peak Power Delivery in Small Form-Factor Sensor Systems

We present a fully integrated energy reservoir unit using a counter flow method for peak power delivery in space-constrained sensor systems. Recent advances in circuits have enabled significant reduction in the size of wireless systems such as implantable biomedical devices. As a consequence, the batteries integrated in these systems have also shrunk, resulting in high internal resistances ( $\sim 10 ~\text{k}\Omega$ ). However, the peak current requirement of power-hungry components such as radios remains in the milliwatt range and hence cannot directly be supplied from the battery. Therefore, an energy reservoir with high output power but small size is required. We present an efficient energy reservoir that dynamically reconfigures a storage capacitor array using a so-called counter flow approach. By creating a voltage gradient on capacitor arrays and moving the capacitors along the slope of the gradient, the supply voltage can be maintained while the energy stored in the reservoir is delivered efficiently to the load. The counter flow energy reservoir delivers 65% of stored energy before recharging is needed which allows up to a $12 \times$ reduction in overall capacitor size compared with our implementation of the previous method. The design supplies up to 13.6-mW output power for $1 ~\mu \text{s}$ . We demonstrate the proposed concept with a pulsed radio, showing an $11.5 \times$ increase in pulse length compared with the previous method.

A New Approach to Evaluate Vinegars Quality: Application of Small Sensor System (S3) Device Coupled with Enfleurage

In this work is illustrated the application of S3 (Small Sensor System) device, equipped with an array of six metal oxide semiconductor (MOX) gas sensors, coupled with enfleurage as new approach to characterize the aromatic profile of Balsamic Vinegars (BVs). Thanks to the enfleurage in fact, the lipophilic volatile compounds are extracted from balsamic vinegar while acetic acid and its derivatives whose high concentration negatively influences MOX sensors sensitivity are not involved in the process. The obtained results show the huge potentiality of this new approach to evaluate BVs quality. All the samples were analyzed in parallel by GC-MS (Gas Chromatography-Mass Spectrometry) with SPME (Solid Phase Micro-Extraction).

Human-driven design of micro- and nanotechnology based future sensor systems

Purpose – This paper aims to present an overview of the various ethical, societal and critical issues that micro- and nanotechnology-based small, energy self-sufficient sensor systems raise in different selected application fields. An ethical approach on the development of these technologies was taken in a very large international, multitechnological European project. The authors approach and methodology are presented in the paper and, based on this review, the authors propose general principles for this kind of work. Design/methodology/approach – The authors’ approach is based on a great amount of experience working together in multi-disciplinary teams. Ethical issues have usually been handled in the authors’ work to some degree. In this project, the authors had the opportunity to emphasise the human view in technological development, utilise the authors’ experience from previous work and customise the authors’ approach to this particular case. In short, the authors created a wide set of application scenarios with technical and application field experts in the authors’ research project. The scenarios were evaluated with external application field experts, potential consumer users and ethics experts. Findings – Based on the authors’ experiences in this project and in previous work, the authors suggest a preliminary model for construction activity within technology development projects. The authors call this model the Human-Driven Design approach, and Ethics by Design as a more focussed sub-set of this approach. As all enabling technologies have both positive and negative usage possibilities, and so-called ethical assessment tends to focus on negative consequences, there are doubts from some stakeholders about including ethical perspectives in a technology development project. Research limitations/implications – The authors argue that the ethical perspective would be more influential if it were to provide a more positive and constructive contribution to the development of technology. The main findings related to the ethical challenges based on the actual work done in this project were the following: the main user concerns were in relation to access to information, digital division and the necessity of all the proposed measurements; the ethics experts highlighted the main ethical issues as privacy, autonomy, user control, freedom, medicalisation and human existence. Practical implications – Various technology assessment models and ethical approaches for technological development have been developed and performed for a long time, and recently, a new approach called Responsible Research and Innovation has been introduced. The authors’ intention is to give a concrete example for further development as a part of the development of this approach. Social implications – The authors’ study in this particular case covers various consumer application possibilities for small sensor systems. The application fields studied include health, well-being, safety, sustainability and empathic user interfaces. The authors believe that the ethical challenges identified are valuable to other researchers and practitioners who are studying and developing sensor-based solutions in similar fields. Originality/value – The authors’ study covers various consumer application possibilities of small sensor systems. The studied application fields include health, well-being, safety, sustainability and empathic user interfaces. The findings are valuable to other researchers and practitioners who are studying and developing sensor-based solutions to similar fields.

Electrode Characteristics of Non-contact Electrocardiographic Measurement

The ability to take electrocardiographic measurements while performing our daily activities has become the people-choice for modern age vital sign sensing. Currently, wet and dry ECG electrodes are known to pose threats like inflammations, allergic reactions, and metal poisoning due to their direct skin interaction. Therefore, the main goal in this work is to implement a very small ECG sensor system with a capacitive coupling, which is able to detect electrical signals of heart at a distance without the conductive gel. The aim of this paper is to design, implement, and characterize the contactless ECG electrodes. Under a careful consideration of factors that affect a capacitive electrode functional integrity, several different sizes of ECG electrodes were designed and tested with a pilot ECG device. A very small cotton-insulated copper tape electrode (<TEX>$2.324cm^2$</TEX>) was finally attained that could detect and measure bioelectric signal at about 500 um of distance from the subject's chest.

Piezoelectric Energy Harvesting from Floor Using Wounded PVDF Films

Energy harvesters of PVDF can be used to power small electrical loads or wireless sensor systems. Simple technologies are sufficient for the fabrication of these harvesting modules. Critical process step is the polarization of the piezoelectric material. Main piezoelectric parameters depend strongly on the polarization material. Particularly, the electric field strength and the polarization temperature influence the remanent polarization of PVDF. Dielectric breakdowns of the film at higher temperatures prevent a sufficient polarization. At least, all modules were polarized at a field strength of 100 – 120 MV/m and a temperature of 90°C.Modules with dimensions of 165mm x 95mm x 1.5mm were used to power a commercial available “development kit for Energy Harvesting Wireless systems” (EnOcean ‘EDK 300’). The modules possess of 20 layers of PVDF. Each module was connected via a standard four diode full rectifier bridge with the development kit EDK 300. Positioned underneath a parquet floor (thickness=10mm), the modules converted mechanical energy of footsteps into electricity. Goal of these investigations were to find out configurations suited to generate a sufficient energy level to supply the operation of the EDK 300. Two capacitors in the development kit are used to start the operation of the kit (C1=470μF) and to store converted energy (C2=0.25F). Already a few steps onto one module were sufficient to charge C1 and to start the operation of the EDK 300. Following steps (&gt;100) produced energy which was stored in C2.

Indoor navigation with foot-mounted strapdown inertial navigation and magnetic sensors [Emerging Opportunities for Localization and Tracking

This article describes a method of navigation for an individual based on traditional inertial navigation system (INS) technology, but with very small and self-contained sensor systems. A conventional INS contains quite accurate, but large and heavy, gyroscopes and accelerometers, and converts the sensed rotations and accelerations into position displacements through an algorithm known as a strapdown navigator. They also, almost without exception, use an error compensation scheme such as a Kalman filter to reduce the error growth in the inertially sensed motion through the use of additional position and velocity data from GPS receivers, other velocity sensors (e.g., air, water, and ground speed), and heading aids such as a magnetic compass. This technology has been successfully used for decades, yet the size, weight, and power requirements of sufficiently accurate inertial systems and velocity sensors have prevented their adoption for personal navigation systems. Now, however, as described in this article, miniature inertial measurement units (IMUs) as light as a few grams are available. When placed on the foot to exploit the brief periods of zero velocity when the foot strikes the ground (obviating the need for additional velocity measurement sensors), these IMUs allow the realization of a conventional Kalman-filter-based aided strapdown inertial navigation system in a device no larger or heavier than a box of matches. A particular advantage of this approach is that no stride modeling is involved with its inherent reliance on the estimation of a forward distance traveled on every step ��� the technique works equally well for any foot motion, something especially critical for soldiers and first responders. Also described is a technique to exploit magnetic sensor orientation data even in indoor environments where local disturbances in the Earth���s magnetic field are significant. By carefully comparing INSderived and magnetically derived heading and orientation, a system can automatically determine when sensed magnetic heading is accurate enough to be useful for additional error compensation.

MF133 歩行器使用時の転倒予測に関する研究(MF13 高齢者の転倒,あたり前のことを知る)

In the study, we propose a risk prediction method which combines a motion prediction method based on a human physical model with a motion inference one that originates in the probability theory for a human falling prediction purpose when an elderly person is using a walking aid. We confirm the effectiveness of the proposed method by experiments using a sensor system attached to a subject. The target is limited to human falling in case he is using a walking aid. The method determines whether he is in the state of safety or danger by use of Hidden Markov Models with his position, velocity, and direction of C.O.G data introduced. Moreover, we developed a small, light-weight, and wireless sensor system attached to the subject, and confirmed the possibility of predicting a subject's fall through our overall proposal.

Measuring orientation of human body segments using miniature gyroscopes and accelerometers

In the medical field, there is a need for small ambulatory sensor systems for measuring the kinematics of body segments. Current methods for ambulatory measurement of body orientation have limited accuracy when the body moves. The aim of the paper was to develop and validate a method for accurate measurement of the orientation of human body segments using an inertial measurement unit (IMU). An IMU containing three single-axis accelerometers and three single-axis micromachined gyroscopes was assembled in a rectangular box, sized 20 x 20 x 30 mm. The presented orientation estimation algorithm continuously corrected orientation estimates obtained by mathematical integration of the 3D angular velocity measured using the gyroscopes. The correction was performed using an inclination estimate continuously obtained using the signal of the 3D accelerometer. This reduces the integration drift that originates from errors in the angular velocity signal. In addition, the gyroscope offset was continuously recalibrated. The method was realised using a Kalman filter that took into account the spectra of the signals involved as well as a fluctuating gyroscope offset. The method was tested for movements of the pelvis, trunk and forearm. Although the problem of integration drift around the global vertical continuously increased in the order of 0.50 degrees s(-1), the inclination estimate was accurate within 3 degrees RMS. It was shown that the gyroscope offset could be estimated continuously during a trial. Using an initial offset error of 1 rad s(-1), after 2 min the off-set error was roughly 5% of the original offset error. Using the Kalman filter described, an accurate and robust system for ambulatory motion recording can be realised.