Reducing chip count with a programmable system on chip in personnel detection using signal scavenging

Our laboratory has implemented a personnel detection system, Smart Carpet, which can detect the walking of older adults. The existing system consists of traditional individual components and chips, leading to a large system size, which is inconvenient. To reduce the number of chips and the size of the system, we have implemented a fully functional hardware system for the Smart Carpet using Programmable System on Chip (PSoC). Using PSoC's functional units, we meet the requirement of smart carpet functionality. Using software, the program can be loaded to PSoC chip to control each component on the chip using in the system. The system implemented by a PSoC has been successfully tested with the PSoC development board. Based on the functional units we need, we have designed the necessary peripherals circuitry for the chip, which I have placed onto a Printed Circuit Board (PCB). The I2C communication with PSoC has been applied to achieve multiple boards working cooperatively. The new design can handle 80 sensors. It enjoys smaller size and scalable with carpet size. The reduction in the total number of IC chips is from 17 to 1 and components from 98 to 56 and the reduction of the system size from about 26.3 square inches to 8.7 square inches

Kinematic assessment for stroke patients in a stroke game and a daily activity recognition and assessment system

Stroke is the leading cause of serious, long-term disabilities among which deficits in motor abilities in arms or legs are most common. Those who suffer a stroke can recover through effective rehabilitation which is delicately personalized. To achieve the best personalization, it is essential for clinicians to monitor patients' health status and recovery progress accurately and consistently. Traditionally, rehabilitation involves patients performing exercises in clinics where clinicians oversee the procedure and evaluate patients' recovery progress. Following the in-clinic visits, additional home practices are tailored and assigned to patients. The in-clinic visits are important to evaluate recovery progress. The information collected can then help clinicians customize home practices for stroke patients. However, as the number of in-clinic sessions is limited by insurance policies, the recovery information collected in-clinic is often insufficient. Meanwhile, the home practice programs report low adherence rates based on historic data. Given that clinicians rely on patients to self-report adherence, the actual adherence rate could be even lower. Despite the limited feedback clinicians could receive, the measurement method is subjective as well. In practice, classic clinical scales are mostly used for assessing the qualities of movements and the recovery status of patients. However, these clinical scales are evaluated subjectively with only moderate inter-rater and intra-rater reliabilities. Taken together, clinicians lack a method to get sufficient and accurate feedback from patients, which limits the extent to which clinicians can personalize treatment plans. This work aims to solve this problem. To help clinicians obtain abundant health information regarding patients' recovery in an objective approach, I've developed a novel kinematic assessment toolchain that consists of two parts. The first part is a tool to evaluate stroke patients' motions collected in a rehabilitation game setting. This kinematic assessment tool utilizes body-tracking in a rehabilitation game. Specifically, a set of upper body assessment measures were proposed and calculated for assessing the movements using skeletal joint data. Statistical analysis was applied to evaluate the quality of upper body motions using the assessment outcomes. Second, to classify and quantify home activities for stroke patients objectively and accurately, I've developed DARAS, a daily activity recognition and assessment system that evaluates daily motions in a home setting. DARAS consists of three main components: daily action logger, action recognition part, and assessment part. The logger is implemented with a Foresite system to record daily activities using depth and skeletal joint data. Daily activity data in a realistic environment were collected from sixteen post-stroke participants. The collection period for each participant lasts three months. An ensemble network for activity recognition and temporal localization was developed to detect and segment the clinically relevant actions from the recorded data. The ensemble network fuses the prediction outputs from customized 3D Convolutional-De-Convolutional, customized Region Convolutional 3D network and a proposed Region Hierarchical Co-occurrence network which learns rich spatial-temporal features from either depth data or joint data. The per-frame precision and the per-action precision were 0.819 and 0.838, respectively, on the validation set. For the recognized actions, the kinematic assessments were performed using the skeletal joint data, as well as the longitudinal assessments. The results showed that, compared with non-stroke participants, stroke participants had slower hand movements, were less active, and tended to perform fewer hand manipulation actions. The assessment outcomes from the proposed toolchain help clinicians to provide more personalized rehabilitation plans that benefit patients.Includes bibliographical references

Investigating the Influence of Task Complexity and Outcome Variety on User Performance in Crowdsourcing Projects

Nowadays many companies leverage crowdsourcing to solve problems in order to reduce cost. The quality of the solution submitted by the participant is especially important for the company, so how to improve participation performance has become an essential research topic. From the perspective of task design, this paper proposes a theoretical model based on the job characteristics model to explore how task complexity and outcome variety affect participation performance through influencing self-efficacy and task meaningfulness. We will collect data through an online experiment to validate our proposed research model in the context of a crowdsourced translation task. Participation performance will be measured with subjective questionnaire and objective translation grades. Findings of this research will have theoretical implications and provide practical guidelines for crowdsourcing projects

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Validation of a Kinect V2 based rehabilitation game.

Interactive technologies are beneficial to stroke recovery as rehabilitation interventions; however, they lack evidence for use as assessment tools. Mystic Isle is a multi-planar full-body rehabilitation game developed using the Microsoft Kinect® V2. It aims to help stroke patients improve their motor function and daily activity performance and to assess the motions of the players. It is important that the assessment results generated from Mystic Isle are accurate. The Kinect V2 has been validated for tracking lower limbs and calculating gait-specific parameters. However, few studies have validated the accuracy of the Kinect® V2 skeleton model in upper-body movements. In this paper, we evaluated the spatial accuracy and measurement validity of a Kinect-based game Mystic Isle in comparison to a gold-standard optical motion capture system, the Vicon system. Thirty participants completed six trials in sitting and standing. Game data from the Kinect sensor and the Vicon system were recorded simultaneously, then filtered and sample rate synchronized. The spatial accuracy was evaluated using Pearson's r correlation coefficient, signal to noise ratio (SNR) and 3D distance difference. Each arm-joint signal had an average correlation coefficient above 0.9 and a SNR above 5. The hip joints data had less stability and a large variation in SNR. Also, the mean 3D distance difference of joints were less than 10 centimeters. For measurement validity, the accuracy was evaluated using mean and standard error of the difference, percentage error, Pearson's r correlation coefficient and intra-class correlation (ICC). Average errors of maximum hand extent of reach were less than 5% and the average errors of mean and maximum velocities were about 10% and less than 5%, respectively. We have demonstrated that Mystic Isle provides accurate measurement and assessment of movement relative to the Vicon system

Pasteurized Akkermansia muciniphila Ameliorate the LPS-Induced Intestinal Barrier Dysfunction via Modulating AMPK and NF-κB through TLR2 in Caco-2 Cells

Akkermansia muciniphila is well known for the amelioration of inflammatory responses and restoration of intestinal barrier function. The beneficial effect of A. muciniphila occurred through contacting Toll-like receptor 2 (TLR2) on intestinal epithelial cells by wall components. In this case, the downstream mechanism of pasteurized A. muciniphila stimulating TLR2 for ameliorated intestinal barrier function is worth investigating. In this study, we evaluated the effect of live and pasteurized A. muciniphila on protecting the barrier dysfunction of Caco-2 intestinal epithelial cells induced by lipopolysaccharide (LPS). We discovered that both live and pasteurized A. muciniphila could attenuate an inflammatory response and improve intestinal barrier integrity in Caco-2 monolayers. We demonstrated that A. muciniphila enhances AMP-activated protein kinase (AMPK) activation and inhibits Nuclear Factor-Kappa B (NF-κB) activation through the stimulation of TLR2. Overall, we provided a specific mechanism for the probiotic effect of A. muciniphila on the intestinal barrier function of Caco-2 cells

北京市农村地区老年人健康管理服务现状研究

Objective To learn current status of health management services in the elderly individuals living in rural areas of Beijing,so as to provide evidence for healthcare improvement.Methods The elderly residents aged 60 or above from several rural districts of Beijing were selected by using multistage random sampling method in January 2013.The health management programme those participants obtained and their satisfactory scale were evaluated.Results A total of 719 of 1 023 (71.3％) individuals had health check-up over the past years.Only 4 subjects (0.4％) obtained mental health management,and 35 (4.9％) finished follow-up studies for chronic diseases.The percent of the elderly who received physical examination,profiles of medical record,health education,medical consultation,health evaluation,cancer screening or vaccination showed statistically significant difference of regional distribution (x2 values were 15.7,39.4,30.5,25.2,24.1,18.4 and 19.3,respectively; all P＜0.05).Sites for health check-up,profiles of medical record and health education were also found to have statistically significant regional distribution difference (all P＜0.05).In ordinal logistic regression analysis,age,occupation,health insurance,self health assessment and health medical affected satisfaction of the respondents with health management.Conclusions Our investigation shows a gap between current health management programme and national standard requirement for equal public health services,and the elderly's satisfaction with health management needs to be improved

Selecting fracturing interval for the exploitation of tight oil reservoirs from logs: a case study

The optimal selection of fracturing interval for the exploitation of tight oil reservoirs is very important for formulating a development program. In this study, the reservoir quality and the reservoir fracability are evaluated, and the criteria for the optimal selection of the fracturing interval are established, using the tight reservoir in the the Qing I Member of Qingshankou Formation in the Daqingzijing Oilfield of China as the study site. The results indicate that the porosity, the oil saturation and the effective thickness of tight reservoir are keys to optimizing the fracturing interval. The brittleness index and the difference coefficient among the horizontal stresses in the reservoir have a strong influence on fracability. The stress difference coefficient in the reservoir is smaller and the reservoir develops microfractures, the complex mesh fractures are easier to occur during fracturing. The stress difference between the reservoir and the surrounding bed is small and the thickness of the surrounding bed is thin, it is easy to communicate with adjacent oil-bearing layers when fracturing