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To meet the increasing needs for ubiquitous healthcare, a mobile phone‐based system for monitoring multiple vital signs is under development. In this paper, design and implementation of the system architecture are described. The hierarchy of this system comprises three layers, which respectively handle multiple vital signs sensing, data/command communication via either wireless or wired means, and healthcare management. The fundamental basis of the sensing layer is a wearable cordless sensor device for monitoring vital signs without discomfort to the user during daily activities. The data communication layer performs bi‐directional information exchange between the sensing layer and the management layer. The uppermost management layer conducts data mining and analysis for risk factors assessment and healthcare. Overall considerations of implementation method and prototype fabrication are outlined. Finally, applicability to a variety of real‐world situations, and provision of customizable solutions not only for home healthcare but also for other vital signs‐related domains (such as emergency rescue and safety guarantee) are discussed. Three of the most promising applications based upon this system are described.

The purpose of this paper is to develop a health monitoring system that can measure human vital signs and recognize human activity based on body sensor network (BSN).

The system is mainly composed of electrocardiogram (ECG) signal collection node, blood oxygen signal collection node, inertial sensor node, receiving node and upper computer software. The three collection nodes collect ECG signals, blood oxygen signals and motion signals. And then collected signals are transmitted wirelessly to receiving node and analyzed by software in upper computer in real-time.

Experiment results show that the system can simultaneously monitor human ECG, heart rate, pulse rate, SpO₂ and recognize human activity. A classifier based on coupled hidden Markov model (CHMM) is adopted to recognize human activity. The average recognition accuracy of CHMM classifier is 94.8 percent, which is higher than some existent methods, such as supported vector machine (SVM), C4.5 decision tree and naive Bayes classifier (NBC).

The monitoring system may be used for falling detection, elderly care, postoperative care, rehabilitation training, sports training and other fields in the future.

First, the system can measure human vital signs (ECG, blood pressure, pulse rate, SpO₂, temperature, heart rate) and recognizes some specific simple or complex activities (sitting, lying, go boating, bicycle riding). Second, the researches of using CHMM for activity recognition based on BSN are extremely few. Consequently, the classifier based on CHMM is adopted to recognize activity with ideal recognition accuracies in this paper.

The purpose of this paper is to design a low-power human physiological parameters monitoring system which can monitor six vital parameters simultaneously based on wearable body sensor network.

This paper presents a low-power multiple physiological parameters monitoring system (MPMS) which comprises four subsystems. These are: electrocardiogram (ECG)/respiration (RESP) parameters monitoring subsystem with embedded algorithms; blood oxygen (SpO₂)/pulse rate (PR)/body temperature (BT)/blood pressure (BP) parameters monitoring subsystem with embedded algorithms; main control subsystem which is in charge of system-level power management, communication and interaction design; and upper computer software subsystem which manipulates system function and analyzes data.

Results have successfully demonstrated monitoring human ECG, RESP, PR, SpO₂, BP and BT simultaneously using the MPMS device. In addition, the power reduction technique developed in this work at the physical/hardware level is effective. Reliability of algorithms developed for monitoring these parameters is assessed by Fluke Prosim8 Vital Signs Simulators (produced by Fluke Corp. USA).

The MPMS device provides long-term health monitoring without interference from normal personal activities, which potentially allows applications in real-time daily healthcare monitoring, chronic diseases monitoring, elderly monitoring, human emotions recognization and so on.

First, a power reduction technique at the physical/hardware level is designed to realize low power consumption. Second, the proposed MPMS device enables simultaneously monitoring six key parameters. Third, unlike most monitoring systems in bulk size, the proposed system is much smaller (118 × 58 × 18.5 mm3, 140 g total weight). In addition, a comfortable smart shirt is fabricated to accommodate the portable device, offering reliable measurements.

The purpose of this study is to develop an efficient prediction model using vital signs and standard medical score systems, which predicts the clinical severity level of the patient in advance based on the quick sequential organ failure assessment (qSOFA) medical score method.

To predict the clinical severity level of the patient in advance, the authors have formulated a training dataset that is constructed based on the qSOFA medical score method. Further, along with the multiple vital signs, different standard medical scores and their correlation features are used to build and improve the accuracy of the prediction model. It is made sure that the constructed training set is suitable for the severity level prediction because the formulated dataset has different clusters each corresponding to different severity levels according to qSOFA score.

From the experimental result, it is found that the inclusion of the standard medical scores and their correlation along with multiple vital signs improves the accuracy of the clinical severity level prediction model. In addition, the authors showed that the training dataset formulated from the temporal data (which includes vital signs and medical scores) based on the qSOFA medical scoring system has the clusters which correspond to each severity level in qSOFA score. Finally, it is found that RAndom k-labELsets multi-label classification performs better prediction of severity level compared to neural network-based multi-label classification.

This paper helps in identifying patient' clinical status.

The purpose of the paper is to serve as a useful reference for anyone embarking on research into intellectual capital (IC). It provides a succinct summary of the seminal works on this research area.

The paper reviews the seminal literature arranges it into a chronology of the evolving research into IC.

The findings show that IC has undergone a number of development stages from definitions, models through to measures and applications of IC to business and management issues.

The review is limited to refereed journals and books published before March 2007.

IC is an area of interest to numerous parties, including shareholders, institutional investors, scholars, policymakers and managers. This paper serves as a useful reference on the stages of development of IC and the applications to business and management issues.

The study of IC has undergone a number of stages, from early conscious awareness efforts, to classification of IC and to the search for appropriate measures of IC. This paper provides a taxonomy on IC research as suggestions about future research directions.

A pilot project was initiated in Wrexham in North Wales with two groups of patients suffering from Chronic Obstructive Pulmonary Disease (COPD). One group was provided with a commercial telehealth system (HomMed Genesis) while the other received a medical telecare service involving standalone vital signs peripherals and a phone call from a respiratory nurse who collected data and entered them into a spreadsheet. After four months of monitoring, the outcomes were analysed for both groups and were found to be largely similar both in terms of the interventions, and the perceived quality of life benefits for the patients. A cost benefit analysis showed that the savings to the NHS exceeded the project costs by about £9,000 thanks mainly to a reduction in the number of exacerbations exhibited by the patients. It is recommended that this form of telecare may greatly increase the independence of people with a chronic disease or long‐term condition and that further studies need to be initiated to determine which measurement regime is most suitable.

Quality improvement of reproductive health care has been announced as one of five global strategies to accelerate progress toward reproductive health goals. The World Health Organization emphasises the evaluation of structure, procedure and outcome of health services to improve quality of care. This study aims to assess the quality of provided care in labour and delivery units in two selected Kordestan Medical Science University hospitals.

A descriptive study methodology was utilised to assess the quality of care provided to 96 women with normal pregnancies. Two checklists were used to observe procedures of care and structure together with a questionnaire utilised to assess satisfaction ratings of patients. Data were analysed by SPSS 11.5.

Midwifery care was provided in different stages of labour, with the following mean percentages of compatibility with desirable situation: first stage of labour (71.4 per cent), second stage of labour (63.03 per cent), third stage of labour (80.63 per cent) and first 2 hours after labour (70.50 per cent). The lowest scores were related to the domains of “emotional support”, “hand wash” and “assessment of vital signs”.

The paper develops instructions for care provision or promotion of partograph use for continuous monitoring and evaluation of quality of care by managers. Increasing midwifery personnel and providing facilities for accompanied people to improve quality of emotional care can lead to quality improvement, and finally the women's health and satisfaction.

Hidden behind such frequently used phrases as “The system/policy requires …,” “The organization has decided…” is one simple fact. Systems/policies don't drop from the sky etched in stone tablets and organizations don't decide anything. People make decisions and design systems and write policies. Embracing this fact increases the likelihood that the provision of health care emanates from a “care dealership” in contrast to a “car dealership.” Ignoring this fact leads to less humane, less effective, and more costly health care. This chapter will challenge all of us concerned with caring for all of us – from Organizational Development (OD). Practitioners to CEOs to … to … all of us at some point in our lives – to step up to the need to transform our most basic paradigms. To remind ourselves that human beings give birth to, nurture, sustain, and care for that which we call an organization. In so doing, we will be able to begin to act from the premise that a health care organization is itself a living breathing human organism, a “Patient” in need of care. The quality of care we afford this “Patient” directly and inevitably impacts the quality of care we are afforded as patients. Acting from this premise will transform all of health care, all “care dealerships” … and potentially “car dealerships” as well. OD professionals, therefore, can propel us all to a fourth dimension of caring for all of us.

Improving hospital service access and mothers' care are said to be the best approaches for decreasing maternal mortality. This study aims to evaluate prenatal care (PNC) and suggest ways to improve hospital and health center maternity services.

This was a cross‐sectional descriptive study to evaluate prenatal care services in three domains: service structure; care process; and outcomes. Using non‐randomized quota sampling, 600 PNC clients were assessed in 12 pre‐natal clinics. Two checklists were used to assess facilities and care process and a questionnaire to assess client satisfaction. Validity and reliability were assessed and confirmed.

Six hundred subjects, averaging 29.3 (±9.4) weeks pregnancy, were included. Assessing different care processes demonstrated the following compliance to standards: counseling process 55.5 per cent (±21.2); history‐taking 48.71 per cent (±11.4); vital signs assessment 53.4 per cent (±10.6); general examination 30.2 per cent (±13.3); obstetrical examination 91.8 per cent (±27); blood tests 93.8 per cent (±21.9); urinary tests 86.9 per cent (±26.3); clients' education about peri‐natal‐risk 39.7 per cent (±27.1). Results showed that 0.54 per cent (±13.1) of clients were satisfied with care processes.

Clients and providers were informed about the study's evaluation processes, which may have affected the results.

Study method and results can be used to improve PNC services.

This is the first time a study has focused on Iranian PNC structures, processes and outcomes.

Although conformable devices are commonly designed to couple with the human body for personalized and localized medicine, their applications are expanding rapidly. This paper aims to delineate this expansion and predict greater implications in diverse fields.

Today’s device technologies continue to face fundamental obstacles preventing their seamless integration with target objects to effectively access, evaluate and alter self-specific physical patterns, while still providing physical comfort and enabling continuous data collection. Due to their extreme mechanical compliance, conformable devices permit the query of signals occurring at interfaces so as to decode and encode biological, chemical and mechanical patterns with high resolution, precision and accuracy. These unique and versatile capabilities allow for a marked change in the approach to tackling scientific questions, with the ability to address societal challenges at large.

Here, this study highlights the current state of these devices in a wide range of fields, such as interactive teaching, textiles, robotics, buildings and infrastructure, agriculture, climate and space, and further forecasts essential features of these devices in the near future.

This study justifies conformable devices’ growing utility through a novel quantitative analysis methodology that indexes peer-reviewed journal articles based on specific keywords, whereby this study tracks keyword frequency over time across specific fields in conjunction with conformability-like topics. The resulting trends’ trajectories provide the foundation for this study’s future projections. This study concludes with a perspective on the possible challenges concomitant with a ubiquitous presence of these technologies, including manufacturing, wireless communication, storage, compression, privacy and sharing of data, environmental sustainability, avoidance of inequality and bias and collaboration between stakeholders at all levels of impact.