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With the rapid development of wearable robotics, the requirements for wearable sensors to detect the interaction between wearable robots and humans are increasing. This study proposed a noncontact bendable-sensitive sensor using a semiring optical fiber for monitoring muscle activity. Raw data were from seven subjects with five gaits (four abnormal gaits and one normal gait), and traditional machine learning, e.g., support vector machine (SVM) and ${k}$ nearest neighbors ( ${k}$ -NNs), and big data-driven neural networks, e.g., convolutional neural networks (CNNs), recurrent neural networks (RNNs), and temporal convolutional networks (TCNs), were used to recognize five gaits, due to the complexity of gait-muscle models. Using SVM, ${k}$ -NN, CNN, RNN, and TCN, the average of best recognition accuracies of the proposed sensor was 86.8%, 92%, 96.9%, 99.9%, and 99.4%, respectively. The recognition results suggested that a semiring-optic-fiber (SROF) sensor contained potential information of muscle activity during five gaits, and compared with SVM and ${k}$ -NN, neural networks can better filter and extract features from raw data, and even RNN and TCN models can reach 100% accuracy for certain subjects. This work paves a new way for recognizing abnormal gaits using an SROF sensor.

Flexible sensing exhibits application scenarios in the measurement of muscle deformation and wearable robots. Muscle deformation during exercise is multidirectional, and therefore one of the essential challenges is capturing muscle deformation in multiple directions. In this study, we proposed a wearable sensor of twisted carbon fiber and optical fiber [polymethyl methacrylate (PMMA)] embedded in the fabric, and by converting the light intensity loss to voltage loss, the sensor has the capability to detect muscle activation during movement. The sensor mainly consists of a light-emitting diode (LED), a photodiode to provide and convert light to a voltage signal, a twisted carbon-optic fiber (COF) structure to ensure bending without elongation during deformation under force, and an amplification filter circuit to modulate the signal. A commercial tension sensor was used to verify the relationship between the activation of the vastus medialis and force during calf flexion and extension. Three subjects were employed to complete the experiment, and a correlation coefficient of 0.99 was obtained as well as an experimental average correlation coefficient with a standard deviation of around 0.01. Although influences of the manual manufacturing process are apparent, as well as individual reasons of different subjects, the experimental results suggested that the presented COF sensor can be effectively applied in finding the relationship between vastus medialis activation with tension in calf flexion and extension. We also indicate that the sensor is not sensitive to differences between the right and left legs. This work paves a new way for the design of sensing systems, for example, prostheses and exoskeletons.

AbstractThis work aims to conduct an empirical study on the social benefits of cultural tourism towns featuring the tourism performance industry in the integration of cultural tourism. It combines the BP deep neural network and fuzzy comprehensive analysis method to construct a BP-fuzzy comprehensive evaluation model and applies it to the social empirical investigation of Taiyuan Cultural Tourism Town. In addition, the weights of evaluation indicators such as cultural inheritance and protection, ecological environment improvement and commodity economic development on the development of small towns are calculated. The results show that the weight values of cultural inheritance and protection, ecological environment improvement and commodity economy development on the social results are 0.522, 0.570 and 0.424, respectively. A total of 41.20% of the life benefit G1 is excellent; 39.5% of the environmental benefit of G2 is excellent; and 40.5% of the economic benefit is good. A total of 30.76% of the total social results of the cultural tourism towns are excellent, 37.69% are good, 21.48% are qualified and 10.07% are unqualified. In conclusion, the total social results of TAIYUAN’s cultural tourism town are good. Cultural inheritance and protection, ecological environment improvement and commodity economy development are the key evaluation factors of social results.