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The connectivity analysis of spatially highly resolved data results in networks comprising an immense number of nodes and edges which makes it hard or even impossible to investigate the high-dimensional (HD) network as a whole. A solution to this problem is offered by a connectivity-based segmentation of the HD networks into subsets of functionally similar nodes (network modules) that exhibit pronounced...
This paper proposes a simple method of selecting effective brain local features for age estimation from T1-weighted MR images. We also employ the high-resolution AAL atlas, which is defined by 1,024 local regions, to improve the accuracy of age estimation. We evaluate performance of the proposed method using 1,099 T1-weighted images from a large-scale brain MR image database of healthy Japanese, and...
Recently, rehabilitation treadmills are designed for helping injured persons such as stroke patients and injury athletes in the process of physical therapy. By monitoring the changes of paces and gaits, one can estimate the progress of rehabilitation. At present, most devices that can estimate paces and gaits are wearable and/or expensive. This paper presents an inexpensive, non-intrusive wireless...
A new method to estimate muscle fatigue quantitatively from surface electromyography (EMG) is proposed. The ratio of mean frequency (MNF) to average rectified value (ARV) is used as the index of muscle fatigue, and muscle fatigue is detected when MNF/ARV falls below a pre-determined or pre-calculated baseline. MNF/ARV gives larger distinction between fatigued muscle and non-fatigued muscle. Experiment...
This paper presents a cuff-less hypertension pre-screening device that non-invasively monitors the Blood Pressure (BP) and Heart Rate (HR) continuously. The proposed device simultaneously records two clinically significant and highly correlated biomedical signals, viz., Electrocardiogram (ECG) and Photoplethysmogram (PPG). The device provides a common data acquisition platform that can interface with...
Building on previous experiments in the domain of energy expenditure estimation using wearable sensors, the measurements of energy ratios of a runner on a treadmill were analyzed to observe any commonalities between an inertia measurement unit and an electromyograph sensor. The subjects were equipped with a VO2 gas measurement device, an Inertial Measurement Unit (IMU) measuring gyroscopic activity...
During routine sleep diagnostic procedure, sleep is broadly divided into three states: rapid eye movement (REM), non-REM (NREM) states, and wake, frequently named macro-sleep stages (MSS). In this study, we present a pioneering attempt for MSS detection using full night audio analysis. Our working hypothesis is that there might be differences in sound properties within each MSS due to breathing efforts...
This paper is devoted to the problem of real-time heart rate (HR) response modelling during treadmill exercise. A novel recursive constrained parameter estimation method is developed which in contrast to the conventional parameter estimation schemes (e.g. recursive least squares (RLS) method) can avoid the occurrence of the so-called blowup phenomena. By incorporation of a weighting upon 1) parameter...
Heart Rate Variability (HRV) analysis can be of precious help in most of clinical situations because it is able to quantify the Autonomic Nervous System (ANS) activity. The HRV high frequency (HF) content, related to the parasympathetic tone, reflects the ANS response to an external stimulus responsible of pain, stress or various emotions. We have previously developed the Analgesia Nociception Index...
Spectral analysis of heart rate variability (HRV) is one of the most effective techniques for the assessment of the influence of the autonomic nervous system (ANS) on the heartbeat. Despite its widespread use, it has been demonstrated that HRV subdivision in the low frequency (LF) and high frequency (HF) bands does not accurately reflect separate sympathetic and parasympathetic influences, respectively,...
We present a system for estimating the dental plaque adhesion area using a commercial camera image for oral healthcare via management of the intraoral environment. In recent years, several studies have reported on the relationship between a general disease and a periodontal disease. Such studies mention that normalization of the intraoral environment by tooth brushing is the most important treatment...
This paper reports a simple and reliable electronic technique for the estimation of respiration rate (RR). Giant Magneto-Resistance (GMR) based sensors are employed to extract a plethysmograph signal from the subject. This signal is filtered and processed further through simple signal processing stages to obtain RR indication. The feasibility of the system has been studied on a prototype built and...
The authors developed a wearable finger motion measurement system using inertial and geomagnetic sensors. Using this system, motion and posture of the hands and fingers can be measured. However, the joint center and segment axis cannot be accurately measured in a previous study using the sensors. Therefore, the authors proposed a method of estimating the joint center and segment lengths. This method...
This paper illustrates the effectiveness of generalized partial directed coherence (gPDC) in characterizing time-varying neural connectivity by properly extrapolating its single trial asymptotic statistical results to a multi trial setting. Time-varying estimation is performed with a sliding-window procedure based on the proposal in [1], whereby a time-frequency map of the connectivity between channels...
We propose a novel interpretation of single channel Electroencephalogram (EEG) traces based on the transient nature of encoded processes in the brain. In particular, the proposed framework models EEG as the output of the noisy addition of temporal, reoccurring, transient patterns known as phasic events. This is not only neurophysiologically sound, but it also provides additional information that classical...
In this paper, a method for the assessment of the Unified Parkinson Disease Rating scale (UPDRS) related to tremor is presented. The method described consists of hand resting and posture state detection, tremor detection and tremor quantification based on accelerometer and gyroscope readings from a wrist worn sensor. The initial results on PD patient recordings on home environment indicate the feasibility...
Diagnosis and monitoring of Parkinson's disease has a number of challenges as there is no definitive biomarker despite the broad range of symptoms. Research is ongoing to produce objective measures that can either diagnose Parkinson's or act as an objective decision support tool. Recent research on speech based measures have demonstrated promising results. This study aims to investigate the characteristics...
In this work, we propose a feature exploration method for learning-based cuffless blood pressure measurement. More specifically, to efficiently explore a large feature space from the photoplethysmography signal, we have applied several analytical techniques, including random error elimination, adaptive outlier removal, maximum information coefficient and Pearson's correlation coefficient based feature...
Multimodal fusion is an effective approach to better understand brain disease. To date, most current fusion approaches are unsupervised; there is need for a multivariate method that can adopt prior information to guide multimodal fusion. Here we proposed a novel supervised fusion model, called “MCCAR+jICA”, which enables both identification of multimodal co-alterations and linking the covarying brain...
An adaptive Kalman filter-based fusion algorithm capable of estimating respiration rate for unobtrusive respiratory monitoring is proposed. Using both signal characteristics and a priori information, the Kalman filter is adaptively optimized to improve accuracy. Furthermore, the system is able to combine the respiration-related signals extracted from a textile ECG sensor and an accelerometer to create...
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