Analyzing the impedance of reflection coefficient of S-parameters S11 and S22 using vector network analyzer & recognization of hand gesture using DTW

VNA is commonly used to analyze the network in frequency series and data record by incident and reflection of the small antenna which distributed parallel, the main propose of this research to classify gesture movement based on the reflection coefficient variations of a small antenna. The near field is distributed the hand gesture movement results in unique variations of antenna’s i/p –o/p impedance which can be used to recognize gesture movement of the hands . The two parallel antenna operating at 890 MHz -2.4GHz which is implemented in this research work and VNA is also compatible with this frequency 2.4GHz to collect data in form of S-parameters. First, some movement of hand like boxing, hopping, rowing, and many more gestures are performed and recorded, by measuring S11 and S22 through the antenna. To classify the hand movement based on S11 and S22 variation with the time series, for this dynamic time warping is used. By DTW we find the nearest optimal path of gestures in time series and found the average classification with more accuracies. In this research, we calculate the best impedance matching between the gestures . IndexTerms— Dynamic time warping (DTW) , Vector Network Analysis (VNA), i/p-o/p impedance, gesture movement, optimal path. ________________________________________________________________________________________________________ I. INTRO DUCTION The advance research of sensor technologies allows engineers to use devices to interfacing with human activit ies. Focusing on hand gestures has been interest of everybody in today’s generation because everyone wants to interface with devices without touching of it like in from of wave motion. Due to increases of advancement they want to do work effectively and smarty in less consuming of time. So these application are human computer interface, computer gaming, b iomechanics research, controlling virtual reality, and smart environments also in biomedical science. For example, gesture recognition system may also used as rehabilitation instrument to improve the sensibility of hand for people recovering from physical accidents or physical disabilities [1][2][3][4][7]. For deaf people it also used in sign languages for better communication. Mostly research on topic of gesture recognition, the designers always design the system according to the way of performing the gestures, which depending on different portions of gestures of a person. A VNA is used to record measurement in the indoor, open hallway environment [8][9]. Both transmitting and receiving antennas are connected to VNA by 3 m long coaxial cables [11][12]. Our research goal is used to recognize gesture in time series and find the shortest path between two time series sequences. Dynamic time warping (DTW ) is widely used to gesture recognizing in time series sequences. It compute the best results of all test for best matching of i/p -o/p impedance of given gestures. By DTW, it define between two signals and choosing proper signal for analysis and recognition . all test are done in real and time series. First, make a Yagi–Uda antenna consists of a 10 parallel thin rod elements in a line. Where, all gestures are performing with Two Yagi-Uda antennas (Transmitter & Receiver) kept 15 cm d istant. Connect to VNA to collect the data in S-parameter of reflect ion and incident coefficient of S11 and S22 [13]. There is a single driven element and single Reflector and the antenna works on 2.4GHz frequency which is very suitable for VNA frequency and collected data at fixed frequency i.e., 2.4GHz, with respect to time (10sec). This collected data is used by DTW algorithm in MATLAB. So, the aim of this research is to compute the gesture recognition and find the nearest path of two time series sequence and effectively improving the gesture recognition in real time series . II. PROBLEM FORMULATION VNA is essential tool used for collecting S-parameter (Scattering parameter) of reflected or incident coefficient in high frequency. The frequency range is between 30 KHz -2.4GHz [5][6]. It is difficult to measure total voltage and current at higher frequency, S-parameter. This parameter is very much familiar measurement such as gain, loss reflection /incident coefficient and its impedance. DTW is used to recognize gesture movement and the shortest path of time series. The use of DTW is to recognize hand gestures, in automatic system in cars, rooms, closeopen door, turn on-off light or up – down of music volume . In the medical facilities it use as robotic nursery in future[14][15][6]. In our work we considered the input and output impedance. The impedance analysis provides higher measurement accuracy and stability but it requ ires a costly impedance analyzers so it is suitable only for lower frequency which is used for best impedance matching [20]. DTW is the technique used to find an optimal alignment between two given time dependent sequences. To determine an optimal path one should test every possible warping path between A and B, Each pair of element of sequences A and B, one must obtain the cost matrix . Due to find the optimal pat h November 2017, Volume 4, Issue 11 JETIR (ISSN-2349-5162) JETIR1711013 Journal of Emerging Technologies and Innovative Research (JETIR) www.jetir. org 62 we can used to this for gesture recognition . By the DTW algorithm we can find the nearest optimal path and its gesture to recognize it which is so similar to known gestures [17][19].