• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.1
• /
• pp.109-114
• /
• 2010

In this paper, the implementation of a human signal sensing module that has capabilities to check and restore the weak signals from the human body is presented. A module presented in this paper consists of processing and sensing elements related to human pulse and body temperature and a controller implemented with SoC design method. PPG data is detected by a noise filtering process toward the amplified signal which is from the operating frequency between 0.1Hz - 10Hz. A digital temperature sensor is used to check the body temperature. A sensor outputs the corresponding value of the electric voltage according to the body temperature. Moreover, this paper discusses the implementation of an enhanced microprocessor which is synthesized with VHDL as a part of the SoC development and used to control the entire module. The SoC processor is implemented on a Xilinx Spartan 3 XC3S1000 device and has the achieved operating frequency of 10MHz. The implemented SoC processor core is successfully tested with macro memories in FPGA and the experimental results are hereby shown.

• Journal of Sensor Science and Technology
• /
• v.31 no.6
• /
• pp.411-417
• /
• 2022

In this paper, we propose a sensor with a C-shaped load cell to detect force change when a person sitting on the chair in an electrical transport-convenience vehicle is pushing ground by both heels. The load cell built in the vehicle is mechanically deformed by the vertical force owing to the human weight and the horizontal force by ground-pushing feet. The deformation rate of the load cell and its distribution are simulated using finite element analysis. In the simulation, the applied loads are preset in the range of 10 kg - 100 kg with a step size of 10 kg, and the ground-pushing force by feet is increased to 40 N with a step size of 5 N with respect to each applied load level. The resistance change of the load cell was observed to be linear in simulation as well as in measurement. the maximum difference between simulation and measurement was 0.89 % when the strain gauge constant was 2.243. The constant has a large influence on the difference. The proposed sensor was fabricated by connecting an instrument amplifier and a microcontroller to a load cell and used to detect the force by ground-pushing feet. To detect foot driving, the reference signal was set to 130% of the load, and the duration of the sensor output signal exceeding the reference signal was set to 0.6 s. In a test of a vehicle built with the proposed sensor, the footpushing force by the worker could be successfully detected even when the worker was working.

• Journal of Sensor Science and Technology
• /
• v.27 no.4
• /
• pp.242-248
• /
• 2018

Bicycle fittings have been used to ride bicycles comfortably while minimizing non-traumatic injuries. To analyze the cause of non-traumatic injuries, it is necessary to measure the body weight distribution in various biking positions. In this study, a weight distribution measurement system was implemented by installing five weighable devices on the saddle, both pedals, and both handle grips of a bicycle. To measure the body weight applied through the saddle, the structure of a commercial seat post was modified and a load cell was installed inside. Weighable pedals and handle grips were designed using a 3D modeling program and fabricated by employing a 3D printer. The body weight distribution for ten bicycle riders was measured when the two pedals were aligned horizontally and vertically. Experimental results showed that the body weight distribution varied significantly depending on human body shape, even after the bicycle fitting was completed. The difference between the body weight measured by the proposed system and a commercial scale was less than 3 %.

• Bulletin of the Korean Chemical Society
• /
• v.32 no.12
• /
• pp.4215-4220
• /
• 2011

This study introduces a new concept for a simple, efficient and cheap sensitivity amplification of a Quartz Crystal Microbalance (QCM) based immunosensor system for the detection of tumor necrosis factor-alpha (TNF-${\alpha}$, TNF) by using an in-built magnetic system. The frequency shift due to the applied magnetic field was successfully observed on magnetic particles labeled detection antibodies, anti-human TNF-${\alpha}$, which were bound to the immunologically captured TNF-${\alpha}$ on the gold coated quartz crystals. In the present system, the magnitude of frequency shift depends on both the strength of magnetic field and the amount of target antigen applied. Significant signal amplification was observed when the additional built-in residual stress generated by the modified magnetic particles under the magnetic field applied. Used in conjunction with a sandwich type non-competitive immunoassay format, the lower detection limit was calculated to be 25 $ngmL^{-1}$ and showed good linearity up to TNF-${\alpha}$ concentrations as high as 2.0 ${\mu}gmL^{-1}$. The sensitivity, most importantly, was improved up to 4.3 times compared with the same QCM system which was used only an antigen-antibody binding without additional magnetic amplification.

• Journal of Biomedical Engineering Research
• /
• v.37 no.5
• /
• pp.161-167
• /
• 2016

Recent technological advances in sensor fabrication and bio-signal processing enabled non-constraint and non-intrusive measurement of human bio-signals. Especially, non-constraint measurement of ECG makes it available to estimate various human health parameters such as heart rate. Additionally, non-constraint ECG measurement of wheelchair user provides real-time health parameter information for emergency response. For accurate emergency response with low false alarm rate, it is necessary to discriminate quality levels of ECG measured using non-constraint approach. Health parameters acquired from low quality ECG results in inaccurate information. Thus, in this study, a machine learning based approach for three-class classification of ECG quality level is suggested. Three sensors are embedded in the back seat, chest belt, and handle of automatic wheelchair. For the two sensors embedded in back seat and chest belt, capacitively coupled electrodes were used. The accuracy of quality level classification was estimated using Monte Carlo cross validation. The proposed approach demonstrated accuracy of 94.01%, 95.57%, and 96.94% for each channel of three sensors. Furthermore, the implemented algorithm enables classification of user posture by detection of contacted electrodes. The accuracy for posture estimation was 94.57%. The proposed algorithm will contribute to non-constraint and robust estimation of health parameter of wheelchair users.

• Journal of Sensor Science and Technology
• /
• v.12 no.6
• /
• pp.249-257
• /
• 2003

The bio-telemetry technologies, that use the wireless miniaturized telemetry module implanted in the human body and transmits several biomedical signal from inside to outside of the body, have been expected to solve the problem such as the patient's inconvenience and the limit for diagnosis. In the case of transceiver system using the wireless RF transmission method, the method of three-dimensional localization for implantable miniaturized telemetry module is necessary to detect the exact position of disease. A new method for three-dimensional localization using small loop antenna in the implantable miniaturized telemetry module was proposed in this paper. We proposed a method that can accurately determine the position of telemetry module by analyzing the differences in the strength of signal, which is received at each of the small size RF receiver array installed on the body surface.

• Journal of the Korean Applied Science and Technology
• /
• v.34 no.3
• /
• pp.595-601
• /
• 2017

In vivo assay of glucose detection was described using a skin tattoo film electrode (STF), and the probe was made from carbon nano tube paste modification film paper. Here in the square-wave stripping anodic working range obtained of $20-100mgL^{-1}$ within an accumulation time of 0 seconds only in sea water electrolyte solutions of pH 7.0. The relative standard deviations of 50 mg glucose that were observed of 0.14 % (n=12), respectively, using optimum stripping accumulation of 30 sec, the low detection limit (S/N) was pegged at 15.8 mg/L. The developed results can be applied to the detect of in vivo skin sensing in real time. Which confirms the results are usable for in vitro or vivo diagnostic clinical analysis.

• International journal of advanced smart convergence
• /
• v.7 no.4
• /
• pp.161-168
• /
• 2018

Recently, the bio-sensing information systems for collecting and analysing human body information of a patient in real time in the field of medical information and healthcare information service are continuously increasing. Specially, various wearable devices such as a wrist, a garment, and a skin attachment type for supporting health information of a mobile user are rapidly increasing. Until now, there is no patch-type biometric information service model. Therefore, this paper presents a biometric information system model and the application examples to support biometric information sensing and health information service of mobile user with digital patch system as a new biometric information system. As a result, through this research, research issues based on digital patch system are searched to suggest the direction of continuous research.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.8 no.2
• /
• pp.105-110
• /
• 2008

Human being recognizes emotion fusing information of the other speech signal, expression, gesture and bio-signal. Computer needs technologies that being recognized as human do using combined information. In this paper, we recognized five emotions (normal, happiness, anger, surprise, sadness) through speech signal and facial image, and we propose to method that fusing into emotion for emotion recognition result is applying to multimodal method. Speech signal and facial image does emotion recognition using Principal Component Analysis (PCA) method. And multimodal is fusing into emotion result applying fuzzy membership function. With our experiments, our average emotion recognition rate was 63% by using speech signals, and was 53.4% by using facial images. That is, we know that speech signal offers a better emotion recognition rate than the facial image. We proposed decision fusion method using S-type membership function to heighten the emotion recognition rate. Result of emotion recognition through proposed method, average recognized rate is 70.4%. We could know that decision fusion method offers a better emotion recognition rate than the facial image or speech signal.

• Imaging Science in Dentistry
• /
• v.34 no.4
• /
• pp.185-190
• /
• 2004

Purpose: To compare the diagnostic accuracy for the detection of root fractures in CMOS-based digital periapical images with conventional film-based periapical images. Materials and Methods: Sixty extracted single-root human teeth with closed apices were prepared endodontically and divided into two groups; artificially induced vertical root fracture group and control group. All radiographs were obtained using the paralleling technique. The radiographs were examined by 4 observers three times within a 4 week interval. Receiver operating characteristic (ROC) analysis was carried out using data obtained from four observers. Intra- and inter-examiner agreements were computed using kappa analysis. Results: The area under the ROC curve (Az) was used as an indicator of the diagnostic accuracy of the imaging system. Az values were as follows: direct-digital images; 0.93, film-based images; 0.92, and inverted digital images; 0.91. There was no significant difference between imaging modalities (P<0.05). The kappa value of inter-observer agreement was 0.42 (range: 0.28-0.60) and intra-observer agreement was 0.57 (range: 0.44-0.75). Conclusion : There is no statistical difference in diagnostic accuracy for the detection of vertical root fractures between digital periapical images and conventional periapical images. The results indicate that the CMOS sensor is a good image detector for the evaluation of vertical root fractures.