Electromyography Parameter Variations with Electrocardiography Noise.

Electromyograms (EMG signals) may be contaminated by electrocardiographic (ECG) signals that cannot be easily separated with traditional filters, because both signals have some overlapping spectral components. Therefore, the first challenge encountered in signal processing is to extract the ECG noise from the EMG signal. In this study, the EMG, mixed with different degrees of noise (ECG), is simulated to investigate the variations of the EMG features. Simulated data were derived from the MIT-BIH Noise Stress Test (NSTD) Database. Two EMG and four ECG data were composed with four EMG/ECG SNR to 32 simulated signals. Following Pan-Tompkins R-peak detection, four ECG removal methods were used to remove ECG with different compensation algorithms to obtain the denoised EMG signal. A total of 13 time-domain and four frequency-domain EMG features were calculated from the denoised EMG. In addition, the similarity of denoised EMG features compared to clean EMG was also evaluated. Our results showed that with the ratio EMG/ECG SNR = 10 and 20, the ECG can be almost ignored, and the similarity of EMG features is close to 1. When EMG/ECG SNR = 1 and 2, there is a large variation of EMG features. The results of our simulation study would be beneficial for understanding the variations of EMG features upon the different EMG/ECG SNR.

Empirical Mode Decomposition-Derived Entropy Features Are Beneficial to Distinguish Elderly People with a Falling History on a Force Plate Signal.

Fall risk prediction is an important issue for the elderly. A center of pressure signal, derived from a force plate, is useful for the estimation of body calibration. However, it is still difficult to distinguish elderly people's fall history by using a force plate signal. In this study, older adults with and without a history of falls were recruited to stand still for 60 s on a force plate. Forces in the x, y and z directions (Fx, Fy, and Fz) and center of pressure in the anteroposterior (COPx) and mediolateral directions (COPy) were derived. There were 49 subjects in the non-fall group, with an average age of 71.67 (standard derivation: 6.56). There were also 27 subjects in the fall group, with an average age of 70.66 (standard derivation: 6.38). Five signal series-forces in x, y, z (Fx, Fy, Fz), COPX, and COPy directions-were used. These five signals were further decomposed with empirical mode decomposition (EMD) with seven intrinsic mode functions. Time domain features (mean, standard derivation and coefficient of variations) and entropy features (approximate entropy and sample entropy) of the original signals and EMD-derived signals were extracted. Results showed that features extracted from the raw COP data did not differ significantly between the fall and non-fall groups. There were 10 features extracted using EMD, with significant differences observed among fall and non-fall groups. These included four features from COPx and two features from COPy, Fx and Fz.

Using Eye Tracking to Assess Gaze Concentration in Meditation.

An important component of Heart Chan Meditation is gaze concentration training. Here, we determine whether eye tracking can be used to assess gaze concentration ability. Study participants (n = 306) were requested to focus their gaze on the innermost of three concentric circles for 1 min while their eye movements were recorded. Results suggest that participants with high scores on gaze concentration accuracy and precision had lower systolic blood pressure and higher sleep quality, suggesting that eye tracking may be effective to assess and train gaze concentration within Heart Chan Meditation.

The Evaluation of Physical Stillness with Wearable Chest and Arm Accelerometer during Chan Ding Practice.

Chan Ding training is beneficial to health and emotional wellbeing. More and more people have taken up this practice over the past few years. A major training method of Chan Ding is to focus on the ten Mailuns, i.e., energy points, and to maintain physical stillness. In this article, wireless wearable accelerometers were used to detect physical stillness, and the created physical stillness index (PSI) was also shown. Ninety college students participated in this study. Primarily, accelerometers used on the arms and chest were examined. The results showed that the PSI values on the arms were higher than that of the chest, when participants moved their bodies in three different ways, left-right, anterior-posterior, and hand, movements with natural breathing. Then, they were divided into three groups to practice Chan Ding for approximately thirty minutes. Participants without any Chan Ding experience were in Group I. Participants with one year of Chan Ding experience were in Group II, and participants with over three year of experience were in Group III. The Chinese Happiness Inventory (CHI) was also conducted. Results showed that the PSI of the three groups measured during 20-30 min were 0.123 ± 0.155, 0.012 ± 0.013, and 0.001 ± 0.0003, respectively (p < 0.001 ***). The averaged CHI scores of the three groups were 10.13, 17.17, and 25.53, respectively (p < 0.001 ***). Correlation coefficients between PSI and CHI of the three groups were -0.440, -0.369, and -0.537, respectively (p < 0.01 **). PSI value and the wearable accelerometer that are presently available on the market could be used to evaluate the quality of the physical stillness of the participants during Chan Ding practice.

Consumer Visual and Affective Bias for Soothing Dolls.

Soothing dolls are becoming increasingly popular in a society with a lot of physical and mental stress. Many products are also combined with soothing dolls to stimulate consumers' desire for impulse buying. However, there is no research on the relationship between consumers' purchasing behavior, consumers' preference for soothing dolls, and visual preference. The purpose of this study was to examine the possible factors that affect the emotional and visual preferences of soothing dolls. Two local stores' sales lists were used to extract three different types of dolls. The 2D and 3D versions of these three dolls were used. Subjective emotional preferences were examined by the self-assessment manikin (SAM) scale, with 5-point Likert scales for valence and arousal factors. An eye tracker was used to examine visual preferences, both before and after positive/negative emotion stimulation by the International Affective Picture System (IAPS). There were 37 subjects involved, with an age range of 20-28 years. The experimental results show that the average valence/arousal scores for 2D/3D dolls were (3.80, 3.74) and (2.65, 2.68), respectively. There was no statistical difference, but both 2D and 3D pictures had high valence scores. Eye tracker analysis revealed no gaze difference in visual preference between 2D and 3D dolls. After negative emotional picture stimulation, the observation time of the left-side doll decreased from 2.307 (std 0.905) to 1.947 (std 1.038) seconds, p < 0.001; and that of the right-side picture increased from 1.898 (std 0.907) to 2.252 (std 1.046) seconds, p < 0.001. The average observation time ratio of the eye on the 3D doll was 40.6%, higher than that on the 2D doll (34.3%, p = 0.02). Soothing dolls may be beneficial for emotion relaxation. Soothing dolls always have high valence features according to the SAM evaluation's measurement. Moreover, this study proposes a novel research model using an eye-tracker and the SAM for the SOR framework.

Body massage performance investigation by brain activity analysis.

Massage has been widely applied to improve health and reduce stress. However, the performance difference between hands-on treatment and treatment by mechanical devices has been little mentioned. Therefore, the main aim of this paper is to investigate a subject's EEG performance under massage treatment applied by hand and treatment applied by mechanical devices. Massage was applied to four acupoints for three minutes each. The massage acupoint sequence was from left Jian-wai-yu, right Jian-wai-yu, left Zuo-fei-yu, and finally right Zuo-fei-yu. An EEG system of 32 channels was used. Twenty-four volunteers, mainly college students, were enrolled. EEG rhythm powers of each massage sessions were derived. Two-way ANOVA revealed that there were also significant interactions between the massage stage and the massage type on delta (P < 0.01), theta (P < 0.05), and beta rhythms (P < 0.01), and there were significant differences at different stages for the mechanical massage group (F = 5.557, P < 0.01). The mechanical massage group had more significant differences than the hands-on group for stage coherence of around coherence on alpha rhythm. Further rhythm power scalp topography between two massage methods is also investigated.

A wireless sEMG recording system and its application to muscle fatigue detection.

Surface electromyography (sEMG) is an important measurement for monitoring exercise and fitness. Because if its high sampling frequency requirement, wireless transmission of sEMG data is a challenge. In this article a wireless sEMG measurement system with a sampling frequency of 2 KHz is developed based upon a MSP 430 microcontroller and Bluetooth transmission. Standard isotonic and isometric muscle contraction are clearly represented in the receiving user interface. Muscle fatigue detection is an important application of sEMG. Traditional muscle fatigue is detected from the median frequency of the sEMG power spectrum. The regression slope of the linear regression of median frequency is an important muscle fatigue index. A more negative slope value represents a higher muscle fatigue condition. To test the system performance, muscle fatigue detection was examined by having subjects run on a pedaled-multifunctional elliptical trainer for approximately 30 minutes at three loading levels. Ten subjects underwent a total of 60 exercise sessions to provide the experimental data. Results showed that the regression slope gradually decreases as expected, and there is a significant gender difference.

A wireless accelerometer-based body posture stability detection system and its application for meditation practitioners.

The practice of meditation has become an interesting research issue in recent decades. Meditation is known to be beneficial for health improvement and illness reduction and many studies on meditation have been made, from both the physiological and psychological points of view. It is a fundamental requirement of meditation practice to be able to sit without body motion. In this study, a novel body motion monitoring and estimation system has been developed. A wireless tri-axis accelerometer is used to measure body motion. Both a mean and maximum motion index is derived from the square summation of three axes. Two experiments were conducted in this study. The first experiment was to investigate the motion index baseline among three leg-crossing postures. The second experiment was to observe posture dynamics for thirty minute's meditation. Twenty-six subjects participated in the experiments. In one experiment, thirteen subjects were recruited from an experienced meditation group (meditation experience > 3 years); and the other thirteen subjects were beginners (meditation experience < 1 years). There was a significant posture stability difference between both groups in terms of either mean or maximum parameters (p < 0.05), according to the results of the experiment. Results from another experiment showed that the motion index is different for various postures, such as full-lotus < half-lotus < non-lotus.

Cutoff Point of Mini-Balance Evaluation Systems Test Scores for Elderly Estimated by Center of Pressure Measurements by Linear Regression and Decision Tree Classification.

BACKGROUND: Understanding balance ability and assessing the risk of possible falls are very important for elderly rehabilitation. The Mini-Balanced Evaluation System Test (Mini-BESTest) is an important survey for older adults to evaluate subject balance, but it is not easy to complete due to various limitations of physical activities, including occasional fear of injury. A center of pressure (CoP) signal can be extracted from a force pressure plate with a short recording time, and it is relatively achievable to ask subjects to stand on a force pressure plate in a clinical environment. The goal of this study is to estimate the cutoff score of Mini-BESTest scores from CoP data. METHODS: CoP signals from a human balance evaluation database with data from 75 people were used. Time domain, frequency domain, and nonlinear domain parameters of 60 s CoP signals were extracted to classify different cutoff point scores for both linear regression and a decision tree algorithm. Classification performances were evaluated by accuracy and area under a receiver operating characteristic curve. RESULTS: The correlation coefficient between real and estimated Mini-BESTest scores by linear regression is 0.16. Instead of linear regression, binary classification accuracy above or below a cutoff point score was developed to examine the CoP classification performance for Mini-BESTest scores. The decision tree algorithm is superior to regression analysis among scores from 16 to 20. The highest area under the curve is 0.76 at a cutoff point score of 21 for the CoP measurement condition of eyes opened on the foam, and the corresponding classification accuracy is 76.15%. CONCLUSIONS: CoP measurement is a potential tool to estimate corresponding balance and fall survey scores for elderly rehabilitation and is useful for clinical users.

Aromatherapy benefits autonomic nervous system regulation for elementary school faculty in taiwan.

Workplace stress-related illness is a serious issue, and consequently many stress reduction methods have been investigated. Aromatherapy is especially for populations that work under high stress. Elementary school teachers are a high-stress working population in Taiwan. In this study, fifty-four elementary school teachers were recruited to evaluate aromatherapy performance on stress reduction. Bergamot essential oil was used for aromatherapy spray for 10 minutes. Blood pressure and autonomic nervous system parameters were recorded 5 minutes before and after the application of the aroma spray. Results showed that there were significant decreases in blood pressure, heart rate, LF power percentage, and LF/HF while there were increases in heart rate variability and HF power percentage (P < .001(∗∗∗)) after application of the aromatherapy spray. Further analysis was investigated by dividing subjects into three background variables (position variables, age variables, gender variables) and anxiety degree groups. All parameters were significantly different for most subgroups, except for the substitute teachers and the light-anxiety group. Parasympathetic nervous system activation was measured after aromatherapy in this study. It encouraged further study for other stress working population by aromatherapy.

Wireless portable electrocardiogram and a tri-axis accelerometer implementation and application on sleep activity monitoring.

Night-to-night variability of sleep activity requires more home-based portable sleep monitoring instead of clinical polysomnography examination in the laboratory. In this article, a wireless sleep activity monitoring system is described. The system is light and small for the user. Sleep postures, such as supine or left/right side, were observed by a signal from a tri-axis accelerometer. An overnight electrocardiogram was also recorded with a single lead. Using an MSP430 as microcontroller, both physiological signals were transmitted by a Bluetooth chip. A Labview-based interface demonstrated the recorded signal and sleep posture. Three nights of sleep recordings were used to examine night-to-night variability. The proposed system can record overnight heart rate. Results show that sleep posture and posture change can be precisely detected via tri-axis accelerometer information. There is no significant difference within subject data sets, but there are statistically significant differences among subjects, both for heart rate and for sleep posture distribution. The wireless transmission range is also sufficient for home-based users.

Analysis of Center of Pressure Signals by Using Decision Tree and Empirical Mode Decomposition to Predict Falls among Older Adults.

Falls put older adults at great risk and are related to the body's sense of balance. This study investigated how to detect the possibility of high fall risk subjects among older adults. The original signal is based on center of pressure (COP) measured using a force plate. The falling group includes 29 subjects who had a history of falls in the year preceding this study or had received high scores on the Short Falls Efficacy Scale (FES). The nonfalling group includes 47 enrollees with no history of falls and who had received low scores on the Short FES. The COP in both the anterior-posterior and mediolateral direction were calculated and analyzed through empirical mode decomposition (EMD) up to six levels. The following five features were extracted and imported to a decision tree algorithm: root-mean-square deviation, median frequency, total frequency power, approximate entropy, and sample entropy. The results showed that there were a larger number of statistically different feature parameters, and a higher classification of accuracy was obtained. With the aid of empirical mode decomposition, the average classification accuracy increased 10% and achieved a level of 99.74% in the training group and 96.77% in the testing group, respectively.

Shifted Firefighter Health Investigation by Personal Health Insurance Record in Taiwan.

INTRODUCTION: Taiwan's firefighters use a shift rotation system with 2 days of work and 1 day of rest. Numerous papers have already explored the risks of shift work to the body. However, little data concern the impact of shift work on health as reflected in medical visits. This study used individuals' medical visit record in Taiwan's health insurance system. The locally called "health bank" contains individuals' medical visit record, health insurance payment points and the medicine used. METHODS: Consent was obtained from 150 firefighters who were serving under the shift rotation system to obtain their 2015 individual "My Health Bank" medical data. Comparisons were made between national health insurance data norm. RESULTS: Firefighters make significantly more visits for Western medicine than the annual average (firefighters 6.27 vs norm 5.24, P = 0.04142), more total number of medical visits (9.57 vs 7.75, P = 0.0102), more annual average payment points for Western medicine (4079 vs 2741, P = 0.003151), and a greater average number of total annual medical visit points (7003 vs 4940, p = 0.0003157). Firefighters had significantly higher incidents of respiratory diseases, urogenital diseases, skin and subcutaneous tissue diseases, musculoskeletal system and connective tissue diseases, injuries, and illness from poisoning than did the norm (P<0.05). CONCLUSION: A persuasive health-survey-based method for workers in high occupational hazard industries was proposed in this study, and the result was highly correlated with risk factors of fireworkers. The proposed study method is potential to investigate risk factors of other working.

Arrhythmia ECG noise reduction by ensemble empirical mode decomposition.

A novel noise filtering algorithm based on ensemble empirical mode decomposition (EEMD) is proposed to remove artifacts in electrocardiogram (ECG) traces. Three noise patterns with different power--50 Hz, EMG, and base line wander--were embedded into simulated and real ECG signals. Traditional IIR filter, Wiener filter, empirical mode decomposition (EMD) and EEMD were used to compare filtering performance. Mean square error between clean and filtered ECGs was used as filtering performance indexes. Results showed that high noise reduction is the major advantage of the EEMD based filter, especially on arrhythmia ECGs.

Drug Abuse Research Trend Investigation with Text Mining.

Drug abuse poses great physical and psychological harm to humans, thereby attracting scholarly attention. It often requires experience and time for a researcher, just entering this field, to find an appropriate method to study drug abuse issue. It is crucial for researchers to rapidly understand the existing research on a particular topic and be able to propose an effective new research method. Text mining analysis has been widely applied in recent years, and this study integrated the text mining method into a review of drug abuse research. Through searches for keywords related to the drug abuse, all related publications were identified and downloaded from PubMed. After removing the duplicate and incomplete literature, the retained data were imported for analysis through text mining. A total of 19,843 papers were analyzed, and the text mining technique was used to search for keyword and questionnaire types. The results showed the associations between these questionnaires, with the top five being the Addiction Severity Index (16.44%), the Quality of Life survey (5.01%), the Beck Depression Inventory (3.24%), the Addiction Research Center Inventory (2.81%), and the Profile of Mood States (1.10%). Specifically, the Addiction Severity Index was most commonly used in combination with Quality of Life scales. In conclusion, association analysis is useful to extract core knowledge. Researchers can learn and visualize the latest research trend.

Improvement of Attention in Elementary School Students through Fixation Focus Training Activity.

The attentional problems of school children are a crucial topic due to abundant information in this digital era. There are five attention dimensions for children: focused attention, sustained attention, selective attention, alternating attention, and divided attention. Focused training is a traditional method of improving attention ability. Subjects are required to focus on a fixed point for an extensive period without blinking and to perceive small objects as large. This study investigates which types of attention indicators are influenced by focus training. Eighty-two grade five and six elementary school students (45 experiment group, 37 control group) were involved. The experiment group underwent focus training for 12 weeks. The training was conducted once per week, and the Attention Scales for Elementary School Children were used before and after the training to examine the children's attention. The percentile rank scores of five attention dimensions and the total attention scale were evaluated. The results gave difference data, defined as post-test results minus the pretest results, where significant differences occurred for the total scale (p < 0.05), focused attention (p < 0.05), and selective attention (p < 0.01). Participants also noted that the training helped them improve concentration during school lessons (54.15%), fall asleep (29.1%), and relax the body (8.4%).

Meditation Practice Improves Short-Term Changes in Heart Rate Variability.

BACKGROUND: It is well known that meditation improves the physical and psychological condition of its practitioners. This study investigated the heart rate variability response of meditation practitioners in two Chan master teaching environments, namely face-to-face and video classes. METHODS: Experimental sessions were conducted, one featuring face-to-face classes and the other featuring video classes. The difference in participants' physiological parameters (blood pressure and heart rate variability) between the two experimental sessions was determined. In the first session, physiological parameters were recorded twice, before and after one teaching course, and the second session took place one month after the first. The first and second sessions had 45 and 27 participants, respectively. Those involved in the first experiment had no experience with meditation, whereas participants in the second experiment had practiced meditation for an average of 9 years (range = 1 to 27 years). Both experiments were conducted once a week, with each session lasting 1.5 h. RESULTS: For both experiments, both heart rate and heart rate variability by age significantly decreased after one teaching course. CONCLUSIONS: Chan meditation practitioners benefit from receiving both face-to-face and video class teaching from a Chan master.

An Immunosensor for the Detection of ULBP2 Biomarker.

Pancreatic cancer (PC) is a global health problem that features a very high mortality rate. The UL16 binding protein 2 (ULBP2) is a new biomarker for PC detection. This study develops a simple, reliable, and inexpensive immunosensor for the detection of the ULBP2 antigen while also investigating the effects of an array configuration of connected sensors and zinc oxide (ZnO) nanoparticles on the immunosensor's sensitivity. The ULBP2 antibody was immobilized onto the screen-printed carbon electrode (SPCE) surfaces of three different sensors: a simple SPCE (ULBP2-SPCE); an SPCE array, which is a series of identical SPCE connected to each other at different arrangements of rows and columns (ULBP2-SPCE-1x2 and ULBP2-SPCE-1x3); and an SPCE combined with ZnO nanoparticles (ULBP2-ZnO/SPCE). Impedance spectrum measurements for the immunosensors to ULBP2 antigen were conducted and compared. According to the result, the array configurations (ULBP2-SPCE-1x2 and ULBP2-SPCE-1x3) show an improvement of sensitivity compared to the ULBP2-SPCE alone, but the improvement is not as significant as that of the ULBP2-ZnO/SPCE configuration (ULBP2-ZnO/SPCE > ULBP2-SPCE: 18 times larger). The ULBP2-ZnO/SPCE immunosensor has a low limit of detection (1 pg/mL) and a high sensitivity (332.2 Ω/Log(pg/mL)), excellent linearity (R2 = 0.98), good repeatability (coefficients of variation = 5.03%), and is stable in long-term storage (retaining 95% activity after 28 days storage). In an array configuration, the immunosensor has an increased signal-to-noise ratio (ULBP2-SPCE-1x3 > ULBP2-SPCE: 1.5-fold) and sensitivity (ULBP2-SPCE-1x3 > ULBP2-SPCE: 2.6-fold). In conclusion, either the modification with ZnO nanoparticles onto the sensor or the use of an array configuration of sensors can enhance the immunosensor's sensitivity. In this study, the best immunosensor for detecting ULBP2 antigens is the ULBP2-ZnO/SPCE immunosensor.

A novel compliance measurement in radial arteries using strain-gauge plethysmography.

We propose a novel method for assessing the compliance of the radial artery by using a two-axis mechanism and a standard positioning procedure for detecting the optimal measuring site. A modified sensor was designed to simultaneously measure the arterial diameter change waveform (ADCW) and pressure pulse waveform with a strain gauge and piezoresistor. In the x-axis scanning, the sensor could be placed close to the middle of the radial artery when the ADCW reached the maximum amplitude. In the Z-axis scanning, the contact pressure was continuously increased for data measurement. Upon the deformation of the strain gauge following the change in the vascular cross-section, the ADCW was transferred to the change of the vascular radius. The loaded strain compliance of the radial artery (C(strain)) can be determined by dividing the dynamic changed radius by the pulse pressure. Twenty-three untreated, mild or moderate hypertensive patients aged 29-85 were compared with 14 normotensive patients aged 25-62. The maximum strain compliance between the two groups was significantly different (p < 0.005). Of the hypertensive patients, 14 were at risk of developing hyperlipidemia. There was a significant difference between this and the normotension group (p < 0.005).

Portable obstructive sleep apnea screening system using overnight ECG and a PDA-based wireless transmission system.

Sleep disorders such as obstructive sleep apnea (OSA) are now regarded as an important risk factor for cardiovascular diseases. The increasing demands for home-based sleep monitoring have prompted studies to develop devices that monitor sleep using fewer sensors. This paper proposes an electrocardiogram (ECG)-based sleep monitoring system that uses a personal digital assistant to display signals and a wireless transmission system. An OSA detection algorithm based only on the overnight-ECG-derived heart-rate-variability low-frequency component (0.02-0.04 Hz) exhibited detection sensitivity of 68.97% and specificity of 100%. This system could meet the future demands of home-based sleep monitoring and thereby reduce the current considerable burdens on hospital sleep centers.