Abstract Pain is a highly unpleasant sensory and emotional experience, no objective diagnosis test exists to assess it. In clinical practice there are two main methods for the estimation of pain, patient’s self-report judgement. However, these subjective need biomarkers measure pain important improve management, reduce risk factors, contribute more objective, valid, reliable diagnosis. Therefore, in this study we propose use functional near-infrared spectroscopy (fNIRS) machine learning...

Combining lidar in camera-based simultaneous localization and mapping (SLAM) is an effective method improving overall accuracy, especially at outdoor large scale scenes. Recent development of low-cost lidars (e.g. Livox lidar) enable us to explore such SLAM systems with lower budget higher performance. In this paper we propose CamVox by adapting into visual (ORB-SLAM2) exploring the lidars' unique features. Based on scan pattern lidars, automatic lidar-camera calibration that will work...

Acupuncture is a practice of treatment based on influencing specific points the body by inserting needles. According to traditional Chinese medicine, aim acupuncture for pain management use acupoints relieve excess, activate qi (or vital energy), and improve blood circulation. In this context, Hegu point one most widely-used purpose, it has been linked having an analgesic effect. However, there exists considerable debate as its scientific validity. pilot study, we identify functional...

This paper proposes a new indoor people detection and tracking system using millimeter‐wave (mmWave) radar sensor. Firstly, systematic approach for is presented—a static clutter removal algorithm used removing mmWave data’s points. Two efficient clustering algorithms are to cluster identify in scene. The recursive Kalman filter with data association track multiple simultaneously. Secondly, fast designed based on our proposed algorithms. method lightweight enough scalability portability, we...

The effects of age and gender on EEG signal have been investigated in clinical psychophysiology. However extracting information from data has not addressed. This is useful building automatic systems that can classify a person to or groups based characteristics person, index for searching, identify verify improve brain-computer interface systems. We propose this paper framework classification system using data. also speech-based method extract paralinguistic features contain rich apply these...

Pain diagnosis for nonverbal patients represents a challenge in clinical settings. Neuroimaging methods, such as functional magnetic resonance imaging and near-infrared spectroscopy (fNIRS), have shown promising results to assess neuronal function response nociception pain. Recent studies suggest that neuroimaging conjunction with machine learning models can be used predict different cognitive tasks. The aim of this study is expand previous by exploring the classification fNIRS signals...

Indoor object detection and tracking using millimeter-wave (mmWave) radar sensors have received much attention recently due to the emergence of applications energy assignment, privacy, health, safety. Increasing valid field view system accuracy through multi-sensors is critical achieving an efficient system. This paper uses two mmWave for accurate tracking: noise reduction stages reduce distinguish cluster groups. The presented data fusion method effectively estimates transformation...

Efficient management of large crowded events is always a challenge. Successful such largely depends on the use technologies. There are many business cases where latest technology can vastly improve their management. In recent times, types identification and sensor devices, including RFID tags, have been developed. Such technologies, combined with appropriate backend database systems, be used to crowd event Hajj, an annual pilgrimage Mecca, very unique gathering, which attracts millions...

Artificial Bee Colony (ABC), as a new swarm intelligence based method, suffers from low precision and efficiency in solving optimization problems. Inspired by the improved strategies of Particle Swarm Optimization (PSO), we have proposed some modification on original ABC iteration equation. In this paper, inertial weight is added first item which balances local global searching processes. The contractive parameter also introduced to second instead random number, shows nonlinear descending...

Human identification becomes huge demand in particular for the security related areas. Biometric systems can employ different kinds of features, e.g., features fingerprint, face, iris or posture. EEG signals are signature neural activities. It is confidential and hard to imitate, since a reflection individual-dependent inner mental tasks. has several advantages, such as (i) it corresponds task, (ii) very difficult mimic (iii) almost impossible steal brain activity sensitive stress mood...

In this paper, we present the computation-efficient resource allocation (RA) schemes for millimeter-wave mobile edge computing (mmWave-MEC) system with aid of reconfigurable intelligent surface (RIS), which is used to assist uplink communication from users base station (BS). By means theoretical analysis, achievable rate and computation efficiency (CE) are derived. Then, optimization problem CE maximization under constraints minimum rate, maximum power consumption local CPU frequency...

Radio frequency identification systems with passive tags dramatically increase the ability of an organization to acquire a vast array data about location and properties any entity that can be physically tagged wirelessly scanned within certain technical limitations. However, if multiple are identified simultaneously, messages from collide cancel each other out. One popular anti-collision algorithms is ALOHA-type algorithm, which simple has good performance when number read reasonably small....

Physiological fluctuations are commonly present in functional studies of hemodynamic response such as magnetic resonance imaging (fMRI) and near-infrared spectroscopy (fNIRS). However, the effects these signals neural mechanisms not fully understood. Thus, aim this study is to propose that frequency-specific networks exist somatosensory region within frequency range physiological fluctuations. We used a wavelet coherence approach identify connectivity between cortical regions. Based on...

This paper describes the use of a computational method based on an optical flow algorithm to detect regions interest in near infrared (NIR) spectroscopy. The evaluation such is also presented. Visual inspection and cross correlation analysis NIR cortical activation images were used evaluate our method. visual exposed pain-related activations primary somatosensory cortex (S1) after stimulation which consistent with similar studies, results showed dominant channels both cerebral hemispheres....

This paper presents a new approach for breast cancer diagnosis using combination of an Adaptive Network based Fuzzy Inference System (ANFIS) and the Information Gain method. In this approach, ANFIS is to build input-output mapping both human knowledge machine learning ability information gain method reduce number input features ANFIS. An experimental result shows 98.23% accuracy which underlines capability proposed algorithm.

Extraction of lane markings is still a challenge due to the poor quality and interferences from external circumstances. In this paper, we utilize line segments as low-level features detect on structured road scenes. Our novel algorithm can be highlighted in four items follows. Firstly, surface region reasonably located using adaptive segmentation method, then most circumstances are eliminated by Laplacian filter. Secondly, detected segment detector applied represent structural information...

Brain computer interface is used for human and machine learning analysis. This paper represents the EEG datasets that are built with different cognitive task such as left, right, back front imaginary movement eye open. We have feature extraction method to classify these signal using Support Vector Machine (SVM), k-Nearest Neighbor (k-NN) Artificial Neural Network (ANN). All methods compared other work done datasets. The proposed obtained 95.21% accuracy 98.95% sensitivity SVM k-NN 90.88% ANN...