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.

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.

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.

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.

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.

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.

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%).

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.

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.

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.

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.

Wireless Patrol Sign-In System with Mental Fatigue Detection.

Current sign-in methods of patrolling security guards mainly comprise signature, image identification, and fingerprint identification; notably, none of these methods indicate the physical and mental conditions of such guards. In particular, when patrolling security guards perform their duties consecutively for a long period of time, adequate attention should be directed toward their levels of mental fatigue. When a handwriting sign-in system is adopted, security guards may not record their sign-in time accurately, or they may fake signatures during long shifts. In addition, image identification systems cannot comprehensively reflect the physical and mental statuses of on-duty security guards, particularly their levels of fatigue. Monitor fatigue in patrolling security guards is important to avoid burnout and stress in the workplace. Therefore, in this study, a patrolling sign-in system that integrates physiological signals and images was designed. A thermometer, hand dynamometer, and electromyography sensor were combined to measure physiological signals. Results showed that hand grip strength and the median frequency of electromyography signals gradually reduced when muscle fatigue occurred. The system determined whether a security guard had signed in punctually and whether this person should stay on duty. Overall, this system was verified to operate effectively, and it is therefore applicable for monitoring the sign-in of patrolling security guards who work long shifts. This case series study proposed a conceptual prototype of the system; large-scale testing should be performed in subsequent research.

A Mechanical Sensor Designed for Dynamic Joint Angle Measurement.

Background. The measurement of the functional range of motion (FROM) of lower limb joints is an essential parameter for gait analysis especially in evaluating rehabilitation programs. Aim. To develop a simple, reliable, and affordable mechanical goniometer (MGR) for gait analysis, with six-degree freedom to dynamically assess lower limb joint angles. Design. Randomized control trials, in which a new MGR was developed for the measurements of FROM of lower limb joints. Setting. Reliability of the designed MGR was evaluated and validated by a motion analysis system (MAS). Population. Thirty healthy subjects participated in this study. Methods. Reliability and validity of the new MGR were tested by intraclass correlation coefficient (ICC), Bland-Altman plots, and linear correlation analysis. Results. The MGR has good inter- and intrarater reliability and validity with ICC ≥ 0.93 (for both). Moreover, measurements made by MGR and MAS were comparable and repeatable with each other, as confirmed by Bland-Altman plots. Furthermore, a very high degree of linear correlation (R ≥ 0.92 for all joint angle measurements) was found between the lower limb joint angles measured by MGR and MAS. Conclusion. A simple, reliable, and affordable MGR has been designed and developed to aid clinical assessment and treatment evaluation of gait disorders.

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.

Effects of moderate exercise on relieving mental load of elementary school teachers.

Long-term endurance exercise could increase activity of parasympathetic nervous and decrease activity of sympathetic nervous at rest. However, previous studies all focused on the effect of endurance training on heart rate variability (HRV) for athletes or sedentary subjects. In Taiwan, elementary school teachers teaching and processing the children's and administrative problems always stand and walk. They will sit down only when they review and correct the students' home work. Thus, the goal of this study was to elucidate the beneficial effect of moderate intensity exercise on relieving mental load of elementary school teachers. There were 20 participants in the exercise group and another 20 participants in the nonexercise group. The exercising teachers performed 12 weeks of moderate intensity exercise training for an average of 30 minutes per day, 3 times per week. HRV was measured before and after the 4th, 6th, and 12th weeks. The time and frequency domain parameters of HRV all had significant increases between the beginning and after 12 weeks of training. However, the time and frequency domain parameters of HRV in the nonexercise group had significant decreases between the beginning and after 12 weeks of training. The long-term moderate exercises can relieve mental load of elementary school teachers. Moreover, age was the considerable factor affecting HRV in this study.

The progression of muscle fatigue during exercise estimation with the aid of high-frequency component parameters derived from ensemble empirical mode decomposition.

Muscle fatigue is often monitored via the median frequency derived from the surface electromyography (sEMG) power spectrum during isometric contractions. The power spectrum of sEMG shifting toward lower frequencies can be used to quantify the electromanifestation of muscle fatigue. The dynamic sEMG belongs to a nonstationary signal, which will be affected by the electrode moving, the shift of the muscle, and the change of innervation zone. The goal of this study is to find a more sensitive and stable method in order to sense the progression of muscle fatigue in the local muscle during exercise in healthy people. Five male and five female volunteers participated. Each subject was asked to run on a multifunctional pedaled elliptical trainer for about 30 min, twice a week, and was recorded a total of six times. Three decomposed methods, discrete wavelet transform (DWT), empirical mode decomposition (EMD), and ensemble EMD (EEMD), were used to sense the progression of muscle fatigue. They compared with each other. Although the highest frequency components of sEMG by DWT, EMD, and EEMD have the better performance to sense the progression of muscle fatigue than the raw sEMG, the EEMD has the best performance to reduce nonstationary characteristics and noise of the dynamic sEMG.

Should sleep laboratories have their own predictive formulas for continuous positive airway pressure for patients with obstructive sleep apnea syndrome?

BACKGROUND: Several formulas predicting optimal continuous positive airway pressure (CPAP) for obstructive sleep apnea treatment have been developed and diverse parameters selected as predictive factors in different sleep laboratories using different ethnic groups. This study aimed to validate a constructed predictive formula for the study laboratory and to test the hypothesis that sleep laboratories should have their own predictive formulas. METHODS: Fifty-seven adult subjects with obstructive sleep apnea syndrome (OSAS) were enrolled in the model-building set and underwent two polysomnography (PSG) studies to diagnose OSAS and titrate for optimal CPAP. A predictive formula, derived from anthropometric and polysomnographic variables, was validated together with two other predictive formulas in 30 subjects by comparing the mean predictive CPAP values, rates of successful prediction, and agreements. RESULTS: Regression analysis showed that apnea-hypopnea index (AHI), SaO2nadir (nadir of arterial oxyhemoglobin saturation by pulse oximetry), and body mass index (BMI) strongly correlated with optimal CPAP. The derived predictive formula for the study laboratory was: CPAPpred (predictive CPAP) = 6.380 + 0.033 × AHI - 0.068 × SaO2nadir + 0.171 × BMI (R(2) = 0.335, adjusted R(2) = 0.298). In Taiwan, different predictive formulas used by different sleep laboratories with different independent predictors led to similar mean predictive CPAP values to the mean observed optimal CPAP values, rates of successful prediction, and agreements with the observed optimal CPAP. There were significant differences between the mean predictive CPAP values and mean observed optimal CPAP values, lower rates of successful prediction, and negatively skewed 95% confidence interval (CI) when using a predictive formula derived from different ethnic populations. CONCLUSION: A sleep laboratory may not need to have its own predictive formula for determining the optimal effective CPAP but should adopt the one derived from the same ethnicity of OSAS patients as the reference formula.

The physical effects of aromatherapy in alleviating work-related stress on elementary school teachers in taiwan.

People use aromatherapy to relieve the symptoms of physical and psychological stress. However, previous studies have not precisely clarified a scientific basis for the beneficial effects of aromatherapy. Therefore, the overall purpose of this study was to elucidate the beneficial effect of aromatherapy in relieving work-related stress. Twenty-nine elementary school teachers from Taiwan participated in this study. The experimental procedures comprised 2 phases. First, we verified the effect of aromatherapy by conducting 2 blind tests. We used natural bergamot essential oil extracted from plants and synthesized a chemical essential oil as the placebo to do the aromatherapy. Second, we analyzed the performance of the aromatherapy treatment on the teachers who had various workloads. We measured the teachers' heart rate variability to evaluate their autonomic nervous system activity. The results show that only the natural bergamot essential oil had an effect and that the aromatherapy treatment relieved work-related stress of teachers with various workloads. However, the aromatherapy treatment had a weak effect on young teachers who had a heavy workload. Moreover, the aromatherapy treatment exhibited no effect on teachers who belong to the abnormal body mass index subgroup having a heavy workload.

Exercise muscle fatigue detection system implementation via wireless surface electromyography and empirical mode decomposition.

Surface electromyography (sEMG) is an important measurement for monitoring exercise and fitness. A wireless Bluetooth transmission sEMG measurement system with a sampling frequency of 2 KHz is developed. 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. As fatigue increases, the power spectrum of the sEMG shifts toward lower frequencies. The goal of this study is to evaluate the sensitivity of empirical mode decomposition (EMD) quantifying the electrical manifestations of the local muscle fatigue during exercising in health people. We also compared this method with the raw data and discrete wavelet transform (DWT). Five male and five female volunteers participated. Each subject was asked to run on a multifunctional pedaled elliptical trainer for about 30 minutes, twice a week, and there were a total of six recording times for each subject with a wireless EMG recording system. The results show that sensitivity of the highest frequency component of EMD is better than the highest frequency component of DWT, and raw data.

Characterization of the muscle electrical properties in low back pain patients by electrical impedance myography.

OBJECTIVES: This study aims to investigate the electrical properties of lumbar paraspinal muscles (LPM) of patients with acute lower back pain (LBP) and to study a new approach, namely Electrical Impedance Myography (EIM), for reliable, low-cost, non-invasive, and real-time assessment of muscle-strained acute LBP. DESIGN: Patients with muscle-strained acute LBP (n = 30) are compared to a healthy reference group (n = 30). Electrical properties of LPM are studied. BACKGROUND: EIM is a novel technique under development for the assessment of neuromuscular disease. Therefore, it is speculated that EIM can be employed for the assessment of muscle-strained acute LBP. METHODS: Surface electrodes, in 2-electrode configurations, was used to measure the electrical properties of patient's and healthy subject's LPM at six different frequencies (0.02, 25.02, 50.02, 1000.02, 3000.02, and 5000.02 kHz), with the amplitude of the applied voltage limited to 200 mV. Parameters of impedance (Z), extracellular resistance (Re), intracellular resistance (Ri), and the ratio of extracellular resistance to intracellular resistance (Re/Ri) of LBP patient's and healthy subject's LPM were assessed to see if significant difference in values obtained in muscle-strained acute LBP patients existed. RESULTS: Intraclass correlation coefficient (ICC) showed that all measurements (ICC>0.96 for all studying parameters: Z, Re, Ri, and Re/Ri) had good reliability and validity. Significant differences were found on Z between LBP patient's and healthy subject's LPM at all studying frequencies, with p<0.05 for all frequencies. It was also found that Re (p<0.05) and Re/Ri (p<0.05) of LBP patient's LPM was significant smaller than that of healthy subjects while Ri (p<0.05) of LBP patient's LPM was significant greater than that of healthy subjects. No statistical significant difference was found between the left and right LPM of LBP patients and healthy subjects on the four studying parameters. CONCLUSION: EIM is a promising technique for assessing muscle-strained acute LBP.