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Fulltext BeSafe B2.0 Smart Multisensory Platform for Safety in Workplaces

Márquez-Sánchez S, Campero-Jurado I, Robles-Camarillo D, Rodríguez S, Corchado-Rodríguez JM

Sensors (Basel), 2021 May 12;21(10).
PMID: 34066186 DOI: 10.3390/s21103372

Wearable technologies are becoming a profitable means of monitoring a person's health state, such as heart rate and physical activity. The use of the smartwatch is becoming consolidated, not only as a novelty but also as a very useful tool for daily use. In addition, other devices, such as helmets or belts, are beneficial for monitoring workers and the early detection of any anomaly. They can provide valuable information, especially in work environments, where they help reduce the rate of accidents and occupational diseases, which makes them powerful Personal Protective Equipment (PPE). The constant monitoring of the worker's health can be done in real-time, through temperature, falls, noise, impacts, or heart rate meters, activating an audible and vibrating alarm when an anomaly is detected. The gathered information is transmitted to a server in charge of collecting and processing it. In the first place, this paper provides an exhaustive review of the state of the art on works related to electronics for human activity behavior. After that, a smart multisensory bracelet, combined with other devices, developed a control platform that can improve operators' security in the working environment. Artificial Intelligence and the Internet of Things (AIoT) bring together the information to improve safety on construction sites, power stations, power lines, etc. Real-time and historic data is used to monitor operators' health and a hybrid system between Gaussian Mixture Model and Human Activity Classification. That is, our contribution is also founded on the use of two machine learning models, one based on unsupervised learning and the other one supervised. Where the GMM gave us a performance of 80%, 85%, 70%, and 80% for the 4 classes classified in real time, the LSTM obtained a result under the confusion matrix of 0.769, 0.892, and 0.921 for the carrying-displacing, falls, and walking-standing activities, respectively. This information was sent in real time through the platform that has been used to analyze and process the data in an alarm system.

Matched MeSH terms: Monitoring, Physiologic
Fulltext Saliva-based biosensors: noninvasive monitoring tool for clinical diagnostics

Malon RS, Sadir S, Balakrishnan M, Córcoles EP

Biomed Res Int, 2014;2014:962903.
PMID: 25276835 DOI: 10.1155/2014/962903

Saliva is increasingly recognised as an attractive diagnostic fluid. The presence of various disease signalling salivary biomarkers that accurately reflect normal and disease states in humans and the sampling benefits compared to blood sampling are some of the reasons for this recognition. This explains the burgeoning research field in assay developments and technological advancements for the detection of various salivary biomarkers to improve clinical diagnosis, management, and treatment. This paper reviews the significance of salivary biomarkers for clinical diagnosis and therapeutic applications, with focus on the technologies and biosensing platforms that have been reported for screening these biomarkers.

Matched MeSH terms: Monitoring, Physiologic/methods*
Fulltext Risk of anaesthesia--a review

Tan I, Delilkan AE

Med J Malaysia, 1993 Dec;48(4):381-91.
PMID: 8183160

Modern anaesthesia carries a definite although small risk. The risk from general and regional anaesthesia is reviewed, the causes explored, and preventive strategies discussed. Although anaesthesia may never be 100% safe, a knowledge of the risk and causes enables us to work towards this goal.

Matched MeSH terms: Monitoring, Physiologic
Fulltext A non-printed integrated-circuit textile for wireless theranostics

Yang Y, Wei X, Zhang N, Zheng J, Chen X, Wen Q, et al.

Nat Commun, 2021 08 12;12(1):4876.
PMID: 34385436 DOI: 10.1038/s41467-021-25075-8

While the printed circuit board (PCB) has been widely considered as the building block of integrated electronics, the world is switching to pursue new ways of merging integrated electronic circuits with textiles to create flexible and wearable devices. Herein, as an alternative for PCB, we described a non-printed integrated-circuit textile (NIT) for biomedical and theranostic application via a weaving method. All the devices are built as fibers or interlaced nodes and woven into a deformable textile integrated circuit. Built on an electrochemical gating principle, the fiber-woven-type transistors exhibit superior bending or stretching robustness, and were woven as a textile logical computing module to distinguish different emergencies. A fiber-type sweat sensor was woven with strain and light sensors fibers for simultaneously monitoring body health and the environment. With a photo-rechargeable energy textile based on a detailed power consumption analysis, the woven circuit textile is completely self-powered and capable of both wireless biomedical monitoring and early warning. The NIT could be used as a 24/7 private AI "nurse" for routine healthcare, diabetes monitoring, or emergencies such as hypoglycemia, metabolic alkalosis, and even COVID-19 patient care, a potential future on-body AI hardware and possibly a forerunner to fabric-like computers.

Matched MeSH terms: Monitoring, Physiologic/instrumentation; Monitoring, Physiologic/methods
Fulltext Enabling Remote Health-Caring Utilizing IoT Concept over LTE-Femtocell Networks

Hindia MN, Rahman TA, Ojukwu H, Hanafi EB, Fattouh A

PLoS One, 2016;11(5):e0155077.
PMID: 27152423 DOI: 10.1371/journal.pone.0155077

As the enterprise of the "Internet of Things" is rapidly gaining widespread acceptance, sensors are being deployed in an unrestrained manner around the world to make efficient use of this new technological evolution. A recent survey has shown that sensor deployments over the past decade have increased significantly and has predicted an upsurge in the future growth rate. In health-care services, for instance, sensors are used as a key technology to enable Internet of Things oriented health-care monitoring systems. In this paper, we have proposed a two-stage fundamental approach to facilitate the implementation of such a system. In the first stage, sensors promptly gather together the particle measurements of an android application. Then, in the second stage, the collected data are sent over a Femto-LTE network following a new scheduling technique. The proposed scheduling strategy is used to send the data according to the application's priority. The efficiency of the proposed technique is demonstrated by comparing it with that of well-known algorithms, namely, proportional fairness and exponential proportional fairness.

Matched MeSH terms: Monitoring, Physiologic/methods*
Fulltext Tree Alignment Based on Needleman-Wunsch Algorithm for Sensor Selection in Smart Homes

Chua SL, Foo LK

Sensors (Basel), 2017 Aug 18;17(8).
PMID: 28820438 DOI: 10.3390/s17081902

Activity recognition in smart homes aims to infer the particular activities of the inhabitant, the aim being to monitor their activities and identify any abnormalities, especially for those living alone. In order for a smart home to support its inhabitant, the recognition system needs to learn from observations acquired through sensors. One question that often arises is which sensors are useful and how many sensors are required to accurately recognise the inhabitant's activities? Many wrapper methods have been proposed and remain one of the popular evaluators for sensor selection due to its superior accuracy performance. However, they are prohibitively slow during the evaluation process and may run into the risk of overfitting due to the extent of the search. Motivated by this characteristic, this paper attempts to reduce the cost of the evaluation process and overfitting through tree alignment. The performance of our method is evaluated on two public datasets obtained in two distinct smart home environments.

Matched MeSH terms: Monitoring, Physiologic
Fulltext A Fault Tolerant Surveillance System for Fire Detection and Prevention Using LoRaWAN in Smart Buildings

Safi A, Ahmad Z, Jehangiri AI, Latip R, Zaman SKU, Khan MA, et al.

Sensors (Basel), 2022 Nov 01;22(21).
PMID: 36366109 DOI: 10.3390/s22218411

In recent years, fire detection technologies have helped safeguard lives and property from hazards. Early fire warning methods, such as smoke or gas sensors, are ineffectual. Many fires have caused deaths and property damage. IoT is a fast-growing technology. It contains equipment, buildings, electrical systems, vehicles, and everyday things with computing and sensing capabilities. These objects can be managed and monitored remotely as they are connected to the Internet. In the Internet of Things concept, low-power devices like sensors and controllers are linked together using the concept of Low Power Wide Area Network (LPWAN). Long Range Wide Area Network (LoRaWAN) is an LPWAN product used on the Internet of Things (IoT). It is well suited for networks of things connected to the Internet, where terminals send a minute amount of sensor data over large distances, providing the end terminals with battery lifetimes of years. In this article, we design and implement a LoRaWAN-based system for smart building fire detection and prevention, not reliant upon Wireless Fidelity (Wi-Fi) connection. A LoRa node with a combination of sensors can detect smoke, gas, Liquefied Petroleum Gas (LPG), propane, methane, hydrogen, alcohol, temperature, and humidity. We developed the system in a real-world environment utilizing Wi-Fi Lora 32 boards. The performance is evaluated considering the response time and overall network delay. The tests are carried out in different lengths (0-600 m) and heights above the ground (0-2 m) in an open environment and indoor (1st Floor-3rd floor) environment. We observed that the proposed system outperformed in sensing and data transfer from sensing nodes to the controller boards.

Matched MeSH terms: Monitoring, Physiologic/methods
Pharmacotherapeutic considerations for the management of diabetes mellitus among hospitalized COVID-19 patients

Hasan SS, Kow CS, Bain A, Kavanagh S, Merchant HA, Hadi MA

Expert Opin Pharmacother, 2021 Feb;22(2):229-240.
PMID: 33054481 DOI: 10.1080/14656566.2020.1837114

INTRODUCTION: Diabetes mellitus is one of the most prevalent comorbidities identified in patients with coronavirus disease 2019 (COVID-19). This article aims to discuss the pharmacotherapeutic considerations for the management of diabetes in hospitalized patients with COVID-19.
AREAS COVERED: We discussed various aspects of pharmacotherapeutic management in hospitalized patients with COVID-19: (i) susceptibility and severity of COVID-19 among individuals with diabetes, (ii) glycemic goals for hospitalized patients with COVID-19 and concurrent diabetes, (iii) pharmacological treatment considerations for hospitalized patients with COVID-19 and concurrent diabetes.
EXPERT OPINION: The glycemic goals in patients with COVID-19 and concurrent type 1 (T1DM) or type 2 diabetes (T2DM) are to avoid disruption of stable metabolic state, maintain optimal glycemic control, and prevent adverse glycemic events. Patients with T1DM require insulin therapy at all times to prevent ketosis. The management strategies for patients with T2DM include temporary discontinuation of certain oral antidiabetic agents and consideration for insulin therapy. Patients with T2DM who are relatively stable and able to eat regularly may continue with oral antidiabetic agents if glycemic control is satisfactory. Hyperglycemia may develop in patients with systemic corticosteroid treatment and should be managed upon accordingly.

Matched MeSH terms: Monitoring, Physiologic
Fulltext An Analytical Conductance Model for Gas Detection Based on a Zigzag Carbon Nanotube Sensor

Hosseingholipourasl A, Hafizah Syed Ariffin S, Ahmadi MT, Rahimian Koloor SS, Petrů M, Hamzah A

Sensors (Basel), 2020 Jan 08;20(2).
PMID: 31936402 DOI: 10.3390/s20020357

Recent advances in nanotechnology have revealed the superiority of nanocarbon species such as carbon nanotubes over other conventional materials for gas sensing applications. In this work, analytical modeling of the semiconducting zigzag carbon nanotube field-effect transistor (ZCNT-FET) based sensor for the detection of gas molecules is demonstrated. We propose new analytical models to strongly simulate and investigate the physical and electrical behavior of the ZCNT sensor in the presence of various gas molecules (CO2, H2O, and CH4). Therefore, we start with the modeling of the energy band structure by acquiring the new energy dispersion relation for the ZCNT and introducing the gas adsorption effects to the band structure model. Then, the electrical conductance of the ZCNT is modeled and formulated while the gas adsorption effect is considered in the conductance model. The band structure analysis indicates that, the semiconducting ZCNT experiences band gap variation after the adsorption of the gases. Furthermore, the bandgap variation influences the conductance of the ZCNT and the results exhibit increments of the ZCNT conductance in the presence of target gases while the minimum conductance shifted upward around the neutrality point. Besides, the I-V characteristics of the sensor are extracted from the conductance model and its variations after adsorption of different gas molecules are monitored and investigated. To verify the accuracy of the proposed models, the conductance model is compared with previous experimental and modeling data and a good consensus is observed. It can be concluded that the proposed analytical models can successfully be applied to predict sensor behavior against different gas molecules.

Matched MeSH terms: Monitoring, Physiologic
Real-Time Remote-Health Monitoring Systems: a Review on Patients Prioritisation for Multiple-Chronic Diseases, Taxonomy Analysis, Concerns and Solution Procedure

Mohammed KI, Zaidan AA, Zaidan BB, Albahri OS, Alsalem MA, Albahri AS, et al.

J Med Syst, 2019 Jun 11;43(7):223.
PMID: 31187288 DOI: 10.1007/s10916-019-1362-x

Remotely monitoring a patient's condition is a serious issue and must be addressed. Remote health monitoring systems (RHMS) in telemedicine refers to resources, strategies, methods and installations that enable doctors or other medical professionals to work remotely to consult, diagnose and treat patients. The goal of RHMS is to provide timely medical services at remote areas through telecommunication technologies. Through major advancements in technology, particularly in wireless networking, cloud computing and data storage, RHMS is becoming a feasible aspect of modern medicine. RHMS for the prioritisation of patients with multiple chronic diseases (MCDs) plays an important role in sustainably providing high-quality healthcare services. Further investigations are required to highlight the limitations of the prioritisation of patients with MCDs over a telemedicine environment. This study introduces a comprehensive and inclusive review on the prioritisation of patients with MCDs in telemedicine applications. Furthermore, it presents the challenges and open issues regarding patient prioritisation in telemedicine. The findings of this study are as follows: (1) The limitations and problems of existing patients' prioritisation with MCDs are presented and emphasised. (2) Based on the analysis of the academic literature, an accurate solution for remote prioritisation in a large scale of patients with MCDs was not presented. (3) There is an essential need to produce a new multiple-criteria decision-making theory to address the current problems in the prioritisation of patients with MCDs.

Matched MeSH terms: Monitoring, Physiologic*
Measurement of urine pH and net acid excretion and their association with urine calcium excretion in periparturient dairy cows

Constable PD, Megahed AA, Hiew MWH

J Dairy Sci, 2019 Dec;102(12):11370-11383.
PMID: 31548071 DOI: 10.3168/jds.2019-16805

Urine pH (UpH) and net acid excretion (NAE) are used to monitor the degree of systemic acidification and predict the magnitude of resultant hypercalciuria when feeding an acidogenic ration to control periparturient hypocalcemia in dairy cattle. The objectives of this study were to evaluate the diagnostic performance of urine dipstick and pH paper for measuring UpH, and to characterize the UpH-NAE relationship and the association of urine Ca concentration ([Ca]) with UpH and NAE. Urine samples (n = 1,116) were collected daily from 106 periparturient Holstein-Friesian cows fed an acidogenic ration during late gestation. Net acid excretion was measured by titration, and UpH was measured by a glass-electrode pH meter (reference method), Multistix-SG urine dipsticks (Siemens Medical Solutions Inc., Ann Arbor, MI), and Hydrion pH paper (Micro Essential Laboratory Inc., Brooklyn, NY). Diagnostic performance was evaluated using Spearman correlation coefficient (rs), Bland-Altman plots, and logistic regression. Urine pH measured by urine dipstick (rs = 0.94) and pH paper (rs = 0.96) were strongly associated with UpH. Method-comparison studies indicated that the urine dipstick measured an average of 0.28 pH units higher, and pH paper 0.10 pH units lower, than UpH. Urine [Ca] was more strongly associated with UpH (rs = -0.65) than NAE (rs = 0.52). Goals for controlling periparturient hypocalcemia under the study conditions were UpH <6.22 and <6.11, based on achieving urine [Ca] ≥5 mmol/L and estimated urinary Ca excretion ≥4 g/d, respectively. Urine pH was as accurate at predicting urine [Ca] as NAE when UpH >6.11. We conclude that pH paper is an accurate, practical, and low-cost cow-side test for measuring UpH and provides a clinically useful estimate of urine [Ca].

Matched MeSH terms: Monitoring, Physiologic
Fulltext QOS-aware error recovery in wireless body sensor networks using adaptive network coding

Razzaque MA, Javadi SS, Coulibaly Y, Hira MT

Sensors (Basel), 2014 Dec 29;15(1):440-64.
PMID: 25551485 DOI: 10.3390/s150100440

Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts.

Matched MeSH terms: Monitoring, Physiologic/instrumentation
Fulltext Chromozone: iOS-based exercise heart rate application using universal colour-coding system

Adam Linoby, Jamiaton Kusrin, Muhammad Iskandar Asraff, Muhammad Azamuddin Rodzi, Sufyan Zaki, Hosni Hasan

Jurnal Inovasi Malaysia, 2020;4(1):193-208.
MyJurnal

The conventional heart rate monitor is usually developed with a numeric digital display. This numerical view is obviously not practical to be used during exercise. In this study, the iOS-based mobile application, called Chromozone, was developed to monitor heart rate using the universal color-coding system. The heart rate monitor during the exercise is designed to notify the exercise intensity information to users using the three universal color-coded (i.e. green zone: optimal heart rate; yellow zone: heart rate lower than the optimal zone, and red zone: heart rate higher than the optimal zone). Chromozone is programmed to display uniform colors across the smart phone display, which allows users to easily be informed in regards to the state of exercise intensity. The transfer of heart rate data from the chest transmitter to Chromozone application is designed to use Bluetooth Low Energy (BLE) system technology. The heart rate data is then processed by the application to determine the intensity range of exercise training heart rate based on the user’s personal input (i.e. age, gender, fitness levels and training objective). Preliminary analysis found that Chromozone application is effective in delivering real-time exercise intensity heart rate. Chromozone could potentially help athletes, active individuals and clinical populations to monitor and regulate their workout training regime in a more effective and safer manner.

Matched MeSH terms: Monitoring, Physiologic
The impact of heart rate-based drowsiness monitoring on adverse driving events in heavy vehicle drivers under naturalistic conditions

Wolkow AP, Rajaratnam SMW, Wilkinson V, Shee D, Baker A, Lillington T, et al.

Sleep Health, 2020 06;6(3):366-373.
PMID: 32340910 DOI: 10.1016/j.sleh.2020.03.005

OBJECTIVES: This study examined the influence of a wrist-worn heart rate drowsiness detection device on heavy vehicle driver safety and sleep and its ability to predict driving events under naturalistic conditions.
DESIGN: Prospective, non-randomized trial.
SETTING: Naturalistic driving in Malaysia.
PARTICIPANTS: Heavy vehicle drivers in Malaysia were assigned to the Device (n = 25) or Control condition (n = 34).
INTERVENTION: Both conditions were monitored for driving events at work over 4-weeks in Phase 1, and 12-weeks in Phase 2. In Phase 1, the Device condition wore the device operated in the silent mode (i.e., no drowsiness alerts) to examine the accuracy of the device in predicting driving events. In Phase 2, the Device condition wore the device in the active mode to examine if drowsiness alerts from the device influenced the rate of driving events (compared to Phase 1).
MEASUREMENTS: All participants were monitored for harsh braking and harsh acceleration driving events and self-reported sleep duration and sleepiness daily.
RESULTS: There was a significant decrease in the rate of harsh braking events (Rate ratio = 0.48, p

Matched MeSH terms: Monitoring, Physiologic/instrumentation*
Materials and Techniques for Implantable Nutrient Sensing Using Flexible Sensors Integrated with Metal-Organic Frameworks

Ling W, Liew G, Li Y, Hao Y, Pan H, Wang H, et al.

Adv Mater, 2018 Jun;30(23):e1800917.
PMID: 29633379 DOI: 10.1002/adma.201800917

The combination of novel materials with flexible electronic technology may yield new concepts of flexible electronic devices that effectively detect various biological chemicals to facilitate understanding of biological processes and conduct health monitoring. This paper demonstrates single- or multichannel implantable flexible sensors that are surface modified with conductive metal-organic frameworks (MOFs) such as copper-MOF and cobalt-MOF with large surface area, high porosity, and tunable catalysis capability. The sensors can monitor important nutriments such as ascorbicacid, glycine, l-tryptophan (l-Trp), and glucose with detection resolutions of 14.97, 0.71, 4.14, and 54.60 × 10-6 m, respectively. In addition, they offer sensing capability even under extreme deformation and complex surrounding environment with continuous monitoring capability for 20 d due to minimized use of biological active chemicals. Experiments using live cells and animals indicate that the MOF-modified sensors are biologically safe to cells, and can detect l-Trp in blood and interstitial fluid. This work represents the first effort in integrating MOFs with flexible sensors to achieve highly specific and sensitive implantable electrochemical detection and may inspire appearance of more flexible electronic devices with enhanced capability in sensing, energy storage, and catalysis using various properties of MOFs.

Matched MeSH terms: Monitoring, Physiologic
Feasibility of A-mode ultrasound attenuation as a monitoring method of local hyperthermia treatment

Manaf NA, Aziz MN, Ridzuan DS, Mohamad Salim MI, Wahab AA, Lai KW, et al.

Med Biol Eng Comput, 2016 Jun;54(6):967-81.
PMID: 27039402 DOI: 10.1007/s11517-016-1480-2

Recently, there is an increasing interest in the use of local hyperthermia treatment for a variety of clinical applications. The desired therapeutic outcome in local hyperthermia treatment is achieved by raising the local temperature to surpass the tissue coagulation threshold, resulting in tissue necrosis. In oncology, local hyperthermia is used as an effective way to destroy cancerous tissues and is said to have the potential to replace conventional treatment regime like surgery, chemotherapy or radiotherapy. However, the inability to closely monitor temperature elevations from hyperthermia treatment in real time with high accuracy continues to limit its clinical applicability. Local hyperthermia treatment requires real-time monitoring system to observe the progression of the destroyed tissue during and after the treatment. Ultrasound is one of the modalities that have great potential for local hyperthermia monitoring, as it is non-ionizing, convenient and has relatively simple signal processing requirement compared to magnetic resonance imaging and computed tomography. In a two-dimensional ultrasound imaging system, changes in tissue microstructure during local hyperthermia treatment are observed in terms of pixel value analysis extracted from the ultrasound image itself. Although 2D ultrasound has shown to be the most widely used system for monitoring hyperthermia in ultrasound imaging family, 1D ultrasound on the other hand could offer a real-time monitoring and the method enables quantitative measurement to be conducted faster and with simpler measurement instrument. Therefore, this paper proposes a new local hyperthermia monitoring method that is based on one-dimensional ultrasound. Specifically, the study investigates the effect of ultrasound attenuation in normal and pathological breast tissue when the temperature in tissue is varied between 37 and 65 °C during local hyperthermia treatment. Besides that, the total protein content measurement was also conducted to investigate the relationship between attenuation and tissue denaturation level at different temperature ranges. The tissues were grouped according to their histology results, namely normal tissue with large predominance of cells (NPC), cancer tissue with large predominance of cells (CPC) and cancer with high collagen fiber content (CHF). The result shows that the attenuation coefficient of ultrasound measured following the local hyperthermia treatment increases with the increment of collagen fiber content in tissue as the CHF attenuated ultrasound at the highest rate, followed by NPC and CPC. Additionally, the attenuation increment is more pronounced at the temperature over 55 °C. This describes that the ultrasound wave experienced more energy loss when it propagates through a heated tissue as the tissue structure changes due to protein coagulation effect. Additionally, a significant increase in the sensitivity of attenuation to protein denaturation is also observed with the highest sensitivity obtained in monitoring NPC. Overall, it is concluded that one-dimensional ultrasound can be used as a monitoring method of local hyperthermia since its attenuation is very sensitive to the changes in tissue microstructure during hyperthermia.

Matched MeSH terms: Monitoring, Physiologic*
Fulltext The theory and fundamentals of bioimpedance analysis in clinical status monitoring and diagnosis of diseases

Khalil SF, Mohktar MS, Ibrahim F

Sensors (Basel), 2014;14(6):10895-928.
PMID: 24949644 DOI: 10.3390/s140610895

Bioimpedance analysis is a noninvasive, low cost and a commonly used approach for body composition measurements and assessment of clinical condition. There are a variety of methods applied for interpretation of measured bioimpedance data and a wide range of utilizations of bioimpedance in body composition estimation and evaluation of clinical status. This paper reviews the main concepts of bioimpedance measurement techniques including the frequency based, the allocation based, bioimpedance vector analysis and the real time bioimpedance analysis systems. Commonly used prediction equations for body composition assessment and influence of anthropometric measurements, gender, ethnic groups, postures, measurements protocols and electrode artifacts in estimated values are also discussed. In addition, this paper also contributes to the deliberations of bioimpedance analysis assessment of abnormal loss in lean body mass and unbalanced shift in body fluids and to the summary of diagnostic usage in different kinds of conditions such as cardiac, pulmonary, renal, and neural and infection diseases.

Matched MeSH terms: Monitoring, Physiologic/instrumentation*; Monitoring, Physiologic/methods*
Picture of the month. Subcutaneous fat necrosis of the newborn

Yuen NS, Ibrahim SB

Arch Pediatr Adolesc Med, 2011 Jun;165(6):563-4.
PMID: 21646590 DOI: 10.1001/archpediatrics.2011.80-a
Matched MeSH terms: Monitoring, Physiologic/methods
Fulltext Compliance with monitoring standards for anaesthesia in Malaysian hospitals

Khoo TH, Cardosa MS, Inbasegaran K

Med J Malaysia, 1999 Mar;54(1):72-8.
PMID: 10972008

The Malaysian Society of Anaesthesiologists published a document entitled "Recommendations for Standards of Monitoring during Anaesthesia and Recovery" in 1993. This paper examines the results of two surveys, carried out in 1995 and 1996 respectively; to determine compliance with published Monitoring Standards in Malaysian public and private hospitals. In the private sector, compliance with the recommended standards during anaesthesia varied greatly. Of the 28 government hospitals surveyed in 1996, compliance with monitoring standards during anaesthesia was almost 100%. Standards in recovery areas were less than ideal. The majority of anaesthesiologists thought that the current recommended standards were adequate.

Matched MeSH terms: Monitoring, Physiologic/standards*
Fulltext Ambit determination method in estimating rice plant population density

Abu Bakar, B., Abdul Rahman, M.S., Teoh, C.C., Abdullah, M.Z.K., Ismail, R.

Food Research, 2018;2(2):177-182.
MyJurnal

Rice plant population density is a key indicator in determining the crop setting and fertilizer application rate. It is therefore essential that the population density is monitored to ensure that a correct crop management decision is taken. The conventional method of determining plant population is by manually counting the total number of rice plant tillers in a 25 cm x 25 cm square frame. Sampling is done by randomly choosing several different locations within a plot to perform tiller counting. This sampling method is time consuming, labour intensive and costly. An alternative fast estimating method was developed to overcome this issue. The method relies on measuring the outer circumference
or ambit of the contained rice plants in a 25 cm x 25 cm square frame to determine the number of tillers within that square frame. Data samples of rice variety MR219 were collected from rice plots in the Muda granary area, Sungai Limau Dalam, Kedah. The data were taken at 50 days and 70 days after seeding (DAS). A total of 100 data samples were collected for each sampling day. A good correlation was obtained for the variety of 50 DAS and 70 DAS. The model was then verified by taking 100 samples with the latching strap for 50 DAS and 70 DAS. As a result, this technique can be used as a fast, economical and practical alternative to manual tiller counting. The technique can potentially be used in the development of an electronic sensing system to estimate paddy plant population density.

Matched MeSH terms: Monitoring, Physiologic

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