Heart failure (HF) is the end-stage of all cardiac diseases, characterized by high prevalence, high mortality, and heavy social and economic burden. Early warning of HF exacerbation is of great value for outpatient management and reducing readmission rates. Currently, remote dynamic monitoring technology, which captures changes in hemodynamic and physiological parameters of HF patients, has become the primary method for early warning and is a hot research topic in clinical studies. This paper systematically reviews the progress in this field, which was categorized into invasive monitoring based on implanted devices, non-invasive monitoring based on wearable devices, and other monitoring technologies based on audio and video. Invasive monitoring primarily involves direct hemodynamic parameters such as left atrial pressure and pulmonary artery pressure, while non-invasive monitoring covers parameters such as thoracic impedance, electrocardiogram, respiration, and activity levels. These parameters exhibit characteristic changes in the early stages of HF exacerbation. Given the clinical heterogeneity of HF patients, multi-source information fusion analysis can significantly improve the prediction accuracy of early warning models. The results of this study suggest that, compared with invasive monitoring, non-invasive monitoring technology, with its advantages of good patient compliance, ease of operation, and cost-effectiveness, combined with AI-driven multimodal data analysis methods, shows significant clinical application potential in establishing an outpatient management system for HF.
Humans ; Heart Failure/physiopathology* ; Monitoring, Physiologic/methods* ; Wearable Electronic Devices ; Remote Sensing Technology ; Early Diagnosis ; Electrocardiography ; Hemodynamics

To explore the feasibility of using UAV-LiDAR for measuring the leaf area index (LAI) of crop canopies, we employed UAV-LiDAR to scan sugarcane canopies during the tillering and elongation stages, acquiring canopy point cloud data. Subsequently, features such as average row height, projected row area, point cloud density at different canopy layers, and the ratios between these parameters were extracted. Three feature selection methods-partial least squares regression (PLSR), XGBoost feature importance (XGBoost-FI), and random forest-recursive feature elimination (RF-RFE)-were adopted to evaluate and identify the optimal input variables for modeling. With these selected variables, LAI inversion models were developed based on random forest (RF) and adaptive boosting (AdaBoost) algorithms, and their performance was assessed. Among the extracted features, the projected row area S_p and the total row point count C_total exhibited strong correlations with LAI, with correlation coefficients of 0.73 and 0.72, respectively. The AdaBoost-based LAI inversion model, using the projected row area S_p, average height H_avg, mid-layer point cloud density C_m, and total row point count C_total as input variables, achieved the best performance, with a coefficient of determination (R_v²) of 0.713 and a root mean square error (RMSE_v) of 0.25 on the validation set. This study provides an effective method for high-throughput acquisition of LAI in field crops, offering valuable scientific support for sugarcane field management and breeding efforts.
Plant Leaves/growth & development* ; Saccharum/growth & development* ; Algorithms ; Unmanned Aerial Devices ; Remote Sensing Technology/methods* ; Crops, Agricultural/growth & development*

The herbs used as the material for traditional Chinese medicine are mostly planted at mountain areas where there is appropriate weather condition. Due to the complex terrain condition in mountain area, the planting at such places is always associated with a scattered pattern, which inevitably bring difficulty to the work of accurate measurement for the planting area. Advanced research about monitoring the planting area for medicine-herb under complex environmental condition is so critical and meaningful for developing the medicine-herb planting to a large scale and an industry. Therefore, this research, taking the planting of Herpetospermum pedunculosum in Luding county as an example, utilizes RS&GIS: using the image data from TM and ETM datum as the remote sensing information source, integrating GPS data from quadrat survey on the spots, and analyzing on a GIS platform, to extract the planting area of H. pedunculosum in Luding county. The results indicate that: (1) the method and technology used to estimate the planting area of H. pedunculosum are feasible and can be applied to monitoring the planting area of medicine-herb at mountain area under complex environmental conditions: (2) the planting area of H. pedunculosum in Luding county is estimated to be 857. 246 acres by the methods utilized in this research, which is closed to the value from local statistical data with an error range less than 5%; (3) in consideration of those inevitable errorrs generating from the procedures such as remote sensing data acquisition, data preprocessing, data interpretation, and so on, and the fact that the classification of remote sensing data, which must be implemented by those above procedures, was used directly to extract the herb type, the accuracy of area estimation for the herb is significantly influenced by the accuracy of classification for herb type, and the estimated area is inevitably associated with some error.
China ; Cucurbitaceae ; chemistry ; growth & development ; Geographic Information Systems ; Medicine, Tibetan Traditional ; Remote Sensing Technology ; methods

To investigate the resources of medicinal plant, such as wild Apocynum, supervised classification based on Principal Component Analysis (PCA) and texture feature were used to monitor wild medicinal plants from image captured by ZY-3 and World-view-2 and compare which satellite Image are more appropriate to monitor the wild medicinal plants. The research results shows that: for more complex growth conditions wild medicinal plants Apocynum, high-resolution images Worldview-2 is more suitable for its remote identification, the low-resolution satellite ZY-3 can only recognizes the wild medicinal plants which distributed intensively. If the study target distribution is more intensive and larger scale, and cultivated type medicinal plants, the use of satellite ZY-3 in low resolution remote sensing data to identify the target can be a good choice, it is not necessary to buy high-resolution data, in order to avoid waste of expenditure, for the scattered distribution, the high-resolution satellite imagery data may be indispensable to identify targets.
Apocynum ; chemistry ; growth & development ; China ; Conservation of Natural Resources ; Geographic Information Systems ; Plant Dispersal ; Plants, Medicinal ; chemistry ; growth & development ; Remote Sensing Technology ; methods

PATIENTS with chronic heart failure (CHF) have a high incidence of atrial/ventricular arrhythmias which seriously affect life span and quality of life. Cardiac re-synchronization therapy (CRT) can improve cardiac function and reverse myocardial remodeling, therefore improving the quality of life and reducing mortality. CRT with Home-Monitoring (HM) can be used to monitor cardiac arrhythmias and other heart physiological indexes such as intrathoracic impedance and hemodynamics. Through wireless satellites, the data from the patients are sent to a monitor center for analysis. Doctors can identify emergent information and make a rapid diagnosis based on the information stored in the monitor center. CRT with HM has been verified as a valid method to optimize drug treatment according to individual parameters.
Cardiac Resynchronization Therapy ; methods ; Cardiac Resynchronization Therapy Devices ; Chronic Disease ; Heart Failure ; drug therapy ; Heart Function Tests ; Humans ; Remote Sensing Technology ; instrumentation ; methods ; Treatment Outcome

We have developed a new wrist wearing heart rate monitoring alarm apparatus, which can detect the patients' real-time pulse waves. When the abnormal heart rate appears or pulse disappears, the monitoring alarm will sound and dial the remote telephone for help simultaneously. This apparatus uses the switch circuit to control the keyboard of mobile phone, and dials remote telephone in the help of mature technology and communication platform of mobile phones. The intelligent program can distinguish digital pulse signal, pick out the correct cycle of heartbeat intelligently. The new wrist wearing heart rate monitoring alarm apparatus will calculate an average heart rate when it captures consecutively five correct electrocardiograph waveforms. It really provides a simple, inexpensive and effective way for the patients with heart disease.
Automation ; Equipment Design ; Heart Rate ; physiology ; Humans ; Monitoring, Physiologic ; instrumentation ; methods ; Pulse ; Remote Sensing Technology ; instrumentation ; methods ; Signal Processing, Computer-Assisted ; Telemetry ; instrumentation ; methods

To improve accuracy of estimation in planted safflower acreage,we selected agricultural area in Yumin County, Xinjiang as the study area. There safflower was concentrated planted. Supervised classification based on Principal Component Analysis (PCA) and texture feature were used to obtain the safflower acreage from image captured by ZY-3. The classification result was compared with only spectral feature and spectral feature with texture feature. The research result shows that this method can effectively solve the problem of low accuracy and fracture classification result in single data source classification. The overall accuracy is 87.519 1%, which increases by 7.117 2% compared with single data source classification. Therefore, the classification method based on PCA and texture features can be adapted to RS image classification and estimate the acreage of safflower. This study provides a feasible solution for estimation of planted safflower acreage by image captured by ZY-3 satellite.
Algorithms ; Carthamus tinctorius ; chemistry ; growth & development ; Image Processing, Computer-Assisted ; Pattern Recognition, Automated ; Principal Component Analysis ; methods ; Remote Sensing Technology ; methods

With the development of the wireless communication technology, implantable biosensor technology, and embedded system technology, Body Sensor Network (BSN) as one branch of wireless sensor networks and important part of the Internet of things has caught more attention of researchers and enterprises. This paper offers the basic concept of the BSN and analyses the related research. We focus on sensor node and wireless communication technology from perspectives of technology challenges, research advance and development trend in the paper. Besides, we also present a relative overview of domestic and overseas projects for the BSN.
Computer Communication Networks ; instrumentation ; Humans ; Monitoring, Ambulatory ; instrumentation ; Remote Sensing Technology ; instrumentation ; methods ; Signal Processing, Computer-Assisted ; Telemedicine ; instrumentation ; Wireless Technology ; instrumentation

This paper presents a remote controlled multimode micro-stimulator based on the chip nRF24E1, which consists mainly of a micro-control unit (MCU) and a radio frequency (RF) transceiver. This micro-stimulator is very compact (18 mmx28 mm two layer printed circuit board) and light (5 g without battery), and can be carried on the back of a small animal to generate electrical stimuli according to the commands sent from a PC 10 meters away. The performance and effectiveness of the micro-stimulator were validated by in vitro experiments on the sciatic nerve (SN) of the frog, where action potentials (APs) as well as artifacts were observed when the SN was stimulated by the micro-stimulator. It was also shown by in vivo behavioral experiments on operant conditioned reflexes in rats which can be trained to obey auditory instruction cues by turning right or left to receive electrical stimulation ('virtual' reward) of the medial forebrain bundle (MFB) in a maze. The correct response for the rats to obey the instructions increased by three times and reached 93.5% in an average of 5 d. This micro-stimulator can not only be used for training small animals to become an 'animal robot', but also provide a new platform for behavioral and neurophysiological experiments.
Acoustic Stimulation ; Animals ; Behavior Control ; methods ; Conditioning, Operant ; physiology ; Electric Stimulation ; instrumentation ; Equipment Design ; Male ; Medial Forebrain Bundle ; physiology ; Movement ; Rats ; Rats, Sprague-Dawley ; Remote Sensing Technology ; Robotics