Synergy of nanocomposite force myography and optical fiber-based wrist angle sensing for ambiguous sign classification

This paper aims at understanding the capabilities and limitation of combining Nanocomposite Force myography sensors (FMG) and optical fiber sensors in standalone systems and their synergy influence on the classification of ambiguous hand gestures. A set of 10 highly similar hand signs from the fingerspelling of the American sign language is adopted in this study. Force myography (FMG) signals are collected from one healthy subject performing the selected set of gestures with 40 repetitions for each gesture. The K-Tournament Grasshopper Extreme Learner (KTGEL) classifier has been implemented to perform an automated feature selection and hand sign classification with an efficient network size and a high accuracy

Hybrid Hand Sign Recognition for Real-Time Wearable Systems with Ambiguity Reduction

Hand sign recognition (HSR) has emerged as a significant field of research and development in the context of wearable systems and human machine interaction. The aim of this research is to investigate the potential of forearm-attached sensors to recognize hand signs and to propose a novel measurement approach for real-time HSR with reduced ambiguities. Three measurement methods are deeply investigated: Force Myography (FMG), Electrical Impedance Tomography (EIT), and surface Electromyography (EMG). The potential of these methods is evaluated in the context of American Sign Language (ASL). For a comprehensive comparative study, it is important to realize same conditions in the data collection. Therefore, a parallel data acquisition interface has been designed for simultaneous data collection. To assess the methods' capacity to distinguish between different hand signs independent of the classification algorithms, we propose a novel method for evaluating the ambiguities between different hand signs directly from the collected data. The application of this method to the collected data for all subjects shows, that EIT and FMG can better differentiate hand signs. Therefore, an FMG-EIT hybrid HSR method is proposed fusing the classification results of both methods based on their complementarity in solving ambiguous cases. The proposed method is able to achieve an average of real time accuracy of 94.16%, 82.5%, and 71.36% for the proposed fusion method, FMG and EIT respectively.:1 Introduction 2 Theoretical background on hand sign recognition 3 State of the art of hand sign recognition systems 4 Design of hand sign recognition measurement systems 5 Investigation of measurements methods 6 Hybrid FMG-EIT method for hand sign recognition 7 Conclusio

Hybrid Hand Sign Recognition for Real-Time Wearable Systems with Ambiguity Reduction

Hand sign recognition (HSR) has emerged as a significant field of research and development in the context of wearable systems and human machine interaction. The aim of this research is to investigate the potential of forearm-attached sensors to recognize hand signs and to propose a novel measurement approach for real-time HSR with reduced ambiguities. Three measurement methods are deeply investigated: Force Myography (FMG), Electrical Impedance Tomography (EIT), and surface Electromyography (EMG). The potential of these methods is evaluated in the context of American Sign Language (ASL). For a comprehensive comparative study, it is important to realize same conditions in the data collection. Therefore, a parallel data acquisition interface has been designed for simultaneous data collection. To assess the methods' capacity to distinguish between different hand signs independent of the classification algorithms, we propose a novel method for evaluating the ambiguities between different hand signs directly from the collected data. The application of this method to the collected data for all subjects shows, that EIT and FMG can better differentiate hand signs. Therefore, an FMG-EIT hybrid HSR method is proposed fusing the classification results of both methods based on their complementarity in solving ambiguous cases. The proposed method is able to achieve an average of real time accuracy of 94.16%, 82.5%, and 71.36% for the proposed fusion method, FMG and EIT respectively.:1 Introduction 2 Theoretical background on hand sign recognition 3 State of the art of hand sign recognition systems 4 Design of hand sign recognition measurement systems 5 Investigation of measurements methods 6 Hybrid FMG-EIT method for hand sign recognition 7 Conclusio

Comparative Study of Measurement Methods for Embedded Bioimpedance Spectroscopy Systems

Bioimpedance spectroscopy (BIS) is an advanced measurement method for providing information on impedance changes at several frequencies by injecting a low current into a device under test and analyzing the response voltage. Several methods have been elaborated for BIS measurement, calculating impedance with a gain phase detector (GPD), IQ demodulation, and fast Fourier transform (FFT). Although the measurement method has a big influence on the measurement system performance, a systematical comparative study has not been performed yet. In this paper, we compare them based on simulations and experimental studies. To maintain similar conditions in the implementation of all methods, we use the same signal generator followed by a voltage-controlled current source (VCCS) as a signal generator. For performance analysis, three DUTs have been designed to imitate the typical behavior of biological tissues. A laboratory impedance analyzer is used as a reference. The comparison addresses magnitude measurement accuracy, phase measurement accuracy, signal processing, hardware complexity, and power consumption. The result shows that the FFT-based system excels with high accuracy for amplitude and phase measurement while providing the lowest hardware complexity, and power consumption, but it needs a much higher software complexity

Effect of <i>Spirulina platensis</i> Biomass with High Polysaccharides Content on Quality Attributes of Common Carp (<i>Cyprinus carpio</i>) and Common Barbel (<i>Barbus barbus</i>) Fish Burgers

Lately, microalgae have been used as natural additives in fish-transformed products to improve their nutritional quality. In this research, the effects of adding Spirulina platensis at concentrations of 0.5, 1 and 1.5% w/v on both the texture and the sensory characteristics of canned burgers were studied. In fact, the addition of Spirulina platensis to fish burgers improves their nutritional composition. Compared to the results of the other fish burger treatments, the treatments that contain 1% of Spirulina platensis had better texture and sensory properties (p &lt; 0.05). Besides, these treatments showed higher swelling ability as well as water and oil holding capacities, due to the important dietary fibers and polysaccharides contents found in Spirulina platensis. No mold or foodborne pathogens were detected in any of the canned burgers up to 8 months of storage at 4 &#176;C. Furthermore, burgers prepared with Spirulina were distinguished by the lowest mean (a* and b*) values (p &lt; 0.05), which shows that the yellow color gradually diminished towards a greenish color. Because of the presence of polysaccharides and pigments (chlorophylls, carotenoids and phycocyanin), Spirulina platensis considerably ameliorates the antioxidant activities of the newly prepared fish burgers. On the whole, we can conclude that Spirulina platensis can be used as a nutritious additive to produce new fish-based products with high alimentary qualities

Effect of Microalgae Incorporation on Quality Characteristics and Functional and Antioxidant Capacities of Ready-to-Eat Fish Burgers Made from Common Carp (<i>Cyprinus carpio</i>)

Microalgae have been used as natural ingredients to produce functional and nutritional food products. The impact of the addition of Chlorella minutissima, Isochrysis galbana, and Picochlorum sp. at concentrations of 0.5, 1, and 1.5% w/v on the texture and sensory attributes of canned burgers were investigated. The results show that carp formulations containing 1% microalgae show significantly better classification performance for many textural and sensory parameters compared to the rest of the formulations. Also, these treatments had higher swelling ability as well as water and oil holding capacities, thanks to the important dietary fiber and polysaccharide contents found in microalgae. Moreover, microalgae-supplemented burgers were characterized as having low a* and b* values, which made the color appear to be pale orange. Additionally, thanks to its richness in pigments and polysaccharides, microalgae considerably ameliorated the antioxidant activities of the new prepared fish burgers. Thus, microalgae could be used as natural and nutritious ingredient to develop new fish-based products