Error mitigation in LPWAN systems: A study on the efficacy of Hamming-coded RPW.

Rotating Polarization Wave (RPW) is a novel Low Power Wide Area Networks (LPWAN) technology for robust connectivity and extended coverage area as compared to other LPWAN technologies such as LoRa and Sigfox when no error detection and correction is employed. Since, IoT and Machine-to-Machine (M2M) communication demand high reliability, RPW with error correction can significantly enhance the communication reliability for critical IoT and M2M applications. Therefore, this study investigates the performance of RPW with single bit error detection and correction using Hamming codes to avoid substantial overhead. Hamming (7,4) coded RPW shows a remarkable improvement of more than 40% in error performance compared to uncoded RPW thereby making it a suitable candidate for IoT and M2M applications. Error performance of coded RPW outperforms coded Chirp Spread Spectrum (CSS) modulation used in LoRa under multipath conditions by 51%, demonstrating superior adaptability and robustness under dynamic channel conditions. These findings provide valuable insights into the ongoing developments in wireless communication systems whilst reporting Q-RPW model as a new and effective method to address the needs of developing LPWAN and IoT ecosystems.

The expectations and acceptability of a smart nursing home model among Chinese older adults: a mixed methods study.

BACKGROUND: Smart nursing homes (SNHs) integrate advanced technologies, including IoT, digital health, big data, AI, and cloud computing to optimise remote clinical services, monitor abnormal events, enhance decision-making, and support daily activities for older residents, ensuring overall well-being in a safe and cost-effective environment. This study developed and validated a 24-item Expectation and Acceptability of Smart Nursing Homes Questionnaire (EASNH-Q), and examined the levels of expectations and acceptability of SNHs and associated factors among older adults in China. METHODS: This was an exploratory sequential mixed methods study, where the qualitative case study was conducted in Hainan and Dalian, while the survey was conducted in Xi'an, Nanjing, Shenyang, and Xiamen. The validation of EASNH-Q also included exploratory and confirmatory factor analyses. Multinomial logistic regression analysis was used to estimate the determinants of expectations and acceptability of SNHs. RESULTS: The newly developed EASNH-Q uses a Likert Scale ranging from 1 (strongly disagree) to 5 (strongly agree), and underwent validation and refinement from 49 items to the final 24 items. The content validity indices for relevance, comprehensibility, and comprehensiveness were all above 0.95. The expectations and acceptability of SNHs exhibited a strong correlation (r = 0.85, p < 0.01), and good test-retest reliability for expectation (0.90) and acceptability (0.81). The highest tertile of expectations (X2=28.89, p < 0.001) and acceptability (X2=25.64, p < 0.001) towards SNHs were significantly associated with the willingness to relocate to such facilities. Older adults with self-efficacy in applying smart technologies (OR: 28.0) and those expressing a willingness to move to a nursing home (OR: 3.0) were more likely to have the highest tertile of expectations compared to those in the lowest tertile. Similarly, older adults with self-efficacy in applying smart technologies were more likely to be in the highest tertile of acceptability of SNHs (OR: 13.8). CONCLUSIONS: EASNH-Q demonstrated commendable validity, reliability, and stability. The majority of Chinese older adults have high expectations for and accept SNHs. Self-efficacy in applying smart technologies and willingness to relocate to a nursing home associated with high expectations and acceptability of SNHs.

Defining the concepts of a smart nursing home and its potential technology utilities that integrate medical services and are acceptable to stakeholders: a scoping review.

BACKGROUND AND OBJECTIVES: Smart technology in nursing home settings has the potential to elevate an operation that manages more significant number of older residents. However, the concepts, definitions, and types of smart technology, integrated medical services, and stakeholders' acceptability of smart nursing homes are less clear. This scoping review aims to define a smart nursing home and examine the qualitative evidence on technological feasibility, integration of medical services, and acceptability of the stakeholders. METHODS: Comprehensive searches were conducted on stakeholders' websites (Phase 1) and 11 electronic databases (Phase 2), for existing concepts of smart nursing home, on what and how technologies and medical services were implemented in nursing home settings, and acceptability assessment by the stakeholders. The publication year was inclusive from January 1999 to September 2021. The language was limited to English and Chinese. Included articles must report nursing home settings related to older adults ≥ 60 years old with or without medical demands but not bed-bound. Technology Readiness Levels were used to measure the readiness of new technologies and system designs. The analysis was guided by the Framework Method and the smart technology adoption behaviours of elder consumers theoretical model. The results were reported according to the PRISMA-ScR. RESULTS: A total of 177 literature (13 website documents and 164 journal articles) were selected. Smart nursing homes are technology-assisted nursing homes that allow the life enjoyment of their residents. They used IoT, computing technologies, cloud computing, big data and AI, information management systems, and digital health to integrate medical services in monitoring abnormal events, assisting daily living, conducting teleconsultation, managing health information, and improving the interaction between providers and residents. Fifty-five percent of the new technologies were ready for use in nursing homes (levels 6-7), and the remaining were proven the technical feasibility (levels 1-5). Healthcare professionals with higher education, better tech-savviness, fewer years at work, and older adults with more severe illnesses were more acceptable to smart technologies. CONCLUSIONS: Smart nursing homes with integrated medical services have great potential to improve the quality of care and ensure older residents' quality of life.

Analysis and prediction of the major fatty acids in vegetable oils using dielectric spectroscopy at 5-30 MHz.

A dielectric spectroscopy method was applied to determine major fatty acids composition in vegetable oils. Dielectric constants of vegetable oils were measured in the frequency range of 5-30 MHz. After data pre-treatment, prediction models were constructed using partial least squares (PLS) regression between dielectric spectral values and the fatty acids compositions measured by gas chromatography. Generally, the root means square error of validation (RMSECV) was less than 11.23% in the prediction of individual fatty acids. The determination coefficient (R2) between predicted and measured oleic, linoleic, mono-unsaturated, and poly-unsaturated fatty acids were 0.84, 0.77, 0.84, and 0.84, respectively. These results indicated that dielectric spectroscopy coupled with PLS regression could be a promising method for predicting major fatty acid composition in vegetable oils and has the potential to be used for in-situ monitoring systems of daily consumption of dietary fatty acids.

For Better or for Worse? A Scoping Review of the Relationship between Internet Use and Mental Health in Older Adults during the COVID-19 Pandemic.

Older adults were advised to avoid social activities during the outbreak of COVID-19. Consequently, they no longer received the social and emotional support they had gained from such activities. Internet use might be a solution to remedy the situation. Therefore, this scoping review sought to map the literature on Internet use and mental health in the older population during the pandemic to examine the extent and nature of the research. A scoping review was conducted using eight databases-PubMed, Scopus, Ebscohost Medline, Ebscohost Academic Search, Ebscohost CINAHL Plus, Ebscohost Cochrane, Ebscohost Psychology and Behavioural Sciences Collection, and Ebscohost SPORTDiscus, according to PRISMA guidelines. Two pre-tested templates (quantitative and qualitative studies) were developed to extract data and perform descriptive analysis and thematic summary. A total of ten articles met the eligibility criteria. Seven out of ten studies were quantitative, while the remainder were qualitative. Five common themes were identified from all the included studies. Our review revealed that Internet use for communication purposes seems to be associated with better mental health in older adults during the COVID-19 pandemic. Directions for future research and limitations of review are also discussed.

The expectations and acceptability of a smart nursing home model among Chinese elderly people: A mixed methods study protocol.

Nursing homes integrated with smart information such as the Internet of Things, cloud computing, artificial intelligence, and digital health could improve not only the quality of care but also benefit the residents and health professionals by providing effective care and efficient medical services. However, a clear concept of a smart nursing home, the expectations and acceptability from the perspectives of the elderly people and their family members are still unclear. In addition, instruments to measure the expectations and acceptability of a smart nursing home are also lacking. The study aims to explore and determine the levels of these expectations, acceptability and the associated sociodemographic factors. This exploratory sequential mixed methods study comprises a qualitative study which will be conducted through a semi-structured interview to explore the expectations and acceptability of a smart nursing home among Chinese elderly people and their family members (Phase I). Next, a questionnaire will be developed and validated based on the results of a qualitative study in Phase I and a preceding scoping review on smart nursing homes by the same authors (Phase II). Lastly, a nationwide survey will be carried out to examine the levels of expectations and acceptability, and the associated sociodemographic factors with the different categories of expectations and acceptability (Phase III). With a better understanding of the Chinese elderly people's expectations and acceptability of smart technologies in nursing homes, a feasible smart nursing home model that incorporates appropriate technologies, integrates needed medical services and business concepts could be formulated and tested as a solution for the rapidly ageing societies in many developed and developing countries.

An Automated High-Accuracy Detection Scheme for Myocardial Ischemia Based on Multi-Lead Long-Interval ECG and Choi-Williams Time-Frequency Analysis Incorporating a Multi-Class SVM Classifier.

Cardiovascular Disease (CVD) is a primary cause of heart problems such as angina and myocardial ischemia. The detection of the stage of CVD is vital for the prevention of medical complications related to the heart, as they can lead to heart muscle death (known as myocardial infarction). The electrocardiogram (ECG) reflects these cardiac condition changes as electrical signals. However, an accurate interpretation of these waveforms still calls for the expertise of an experienced cardiologist. Several algorithms have been developed to overcome issues in this area. In this study, a new scheme for myocardial ischemia detection with multi-lead long-interval ECG is proposed. This scheme involves an observation of the changes in ischemic-related ECG components (ST segment and PR segment) by way of the Choi-Williams time-frequency distribution to extract ST and PR features. These extracted features are mapped to a multi-class SVM classifier for training in the detection of unknown conditions to determine if they are normal or ischemic. The use of multi-lead ECG for classification and 1 min intervals instead of beats or frames contributes to improved detection performance. The classification process uses the data of 92 normal and 266 patients from four different databases. The proposed scheme delivered an overall result with 99.09% accuracy, 99.49% sensitivity, and 98.44% specificity. The high degree of classification accuracy for the different and unknown data sources used in this study reflects the flexibility, validity, and reliability of this proposed scheme. Additionally, this scheme can assist cardiologists in detecting signal abnormality with robustness and precision, and can even be used for home screening systems to provide rapid evaluation in emergency cases.

Defining the concepts of a smart nursing home and its potential technology utilities that integrate medical services and are acceptable to stakeholders: a scoping review protocol.

INTRODUCTION: Smart technologies, digital health and eHealth have been shown to enhance institutional elderly care. Because of the rapidly ageing societies, information technologies in geriatric healthcare are urgently needed. A lot of innovation in smart healthcare has occurred in the past decade, and its use in nursing care assessment, daily living activities and service management is yet to be defined. More fundamentally, the concepts, definitions and scopes of a smart nursing home are still vague. Thus, this scoping review aims to examine the extent, range (variety) and nature (characteristics) of evidence on the existing smart concepts and feasible healthcare technologies, types of medical services in nursing home settings and acceptability of a smart nursing home by the elderly people ≥60 years old, their caregivers, nursing home operators and government agencies. METHODS AND ANALYSIS: This scoping review will be guided by the smart technology adoption behaviours of elder consumers theoretical model (Elderadopt) by Golant and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews. First, we will conduct an internet search for nursing homes and websites and databases related to the stakeholders to retrieve the definitions, concepts and criteria of a smart nursing home (phase 1). Second, we will conduct an additional systematic electronic database search for published articles on any measures of technological feasibility and integration of medical services in nursing home settings and their acceptability by nursing home residents and caregivers (phase 2). The electronic database search will be carried out from 1999 to 30 September 2020 and limited to works published in English and Chinese languages. For phase 2, the selection of literature is further limited to residents of nursing homes aged ≥60 years old with or without medical needs but are not terminally ill or bed-bound. Qualitative data analysis will follow the Framework Methods and thematic analysis using combined inductive and deductive approaches, conducted by at least two reviewers. ETHICS AND DISSEMINATION: This protocol is registered on osf.io (URL: https://osf.io/qtwz2/). Ethical approval is not necessary as the scoping review is not a primary study, and the information is collected from selected articles that are publicly available sources. All findings will be disseminated at conferences and published in peer-reviewed journals.

Quaternion Model of Higher-Order Rotating Polarization Wave Modulation for High Data Rate M2M LPWAN Communication.

With growing interest in Industry 4.0, machine-to-machine communication (M2M) will become the key enabler for low-power wide area networks (LPWANs) in connecting machines and sensor nodes distributed across a distance in the industrial environment. The choice of modulation and diversity techniques, and the selection of spectrum (licensed/unlicensed) will impact and influence the requirements of wireless M2M systems. Link reliability is one of the most important requirements for LPWAN deployment in industrial scenarios. Rotating Polarization Wave (RPW) system has been recently proposed as an LPWAN solution for reliable M2M communication in high clutter environment and it deploys BPSK modulation with polarization diversity (PD). This paper proposes a new multi-level Rotating Polarization Phase-Shift Keying (RP-MPSK) modulation to provide high data rate and energy efficiency. A novel quaternion model for RPW system (Q-RPW) is also proposed to reduce the complexity in modeling, simulation, and implementation. Results using Q-RPW model show that RP-MPSK modulation offers a high diversity gain over BPSK with second-order diversity. Bit error rate (BER) performance of RP-MPSK modulation compared against other LPWAN modulation like MPSK, FSK and QAM has shown high reliability and substantial improvement in SNR. To overcome the degradation in error performance caused by the proposed higher-order modulation, sampling rates are recommended based on BER performance. BER performance of RP-MPSK under multipath and interference conditions is also investigated.

Performance Evaluation of Time-Frequency Distributions for ECG Signal Analysis.

The non-stationary and multi-frequency nature of biomedical signal activities makes the use of time-frequency distributions (TFDs) for analysis inevitable. Time-frequency analysis provides simultaneous interpretations in both time and frequency domain enabling comprehensive explanation, presentation and interpretation of electrocardiogram (ECG) signals. The diversity of TFDs and specific properties for each type show the need to determine the best TFD for ECG analysis. In this study, a performance evaluation of five TFDs in term of ECG abnormality detection is presented. The detection criteria based on extracted features from most important ECG signal components (QRS) to detect normal and abnormal cases. This is achieved by estimating its energy concentration magnitude using the TFDs. The TFDs analyse ECG signals in one-minute interval instead of conventional time domain approach that analyses based on beat or frame containing several beats. The MIT-BIH normal sinus rhythm ECG database total records of 18 long-term ECG sampled at 128 Hz have been analysed. The tested TFDs include Dual-Tree Wavelet Transform, Spectrogram, Pseudo Wigner-Ville, Choi-Williams, and Born-Jordan. Each record is divided into one-minute slots, which is not considered previously, and analysed. The sample periods (slots) are randomly selected ten minutes interval for each record. This result with 99.44% detection accuracy for 15,735 ECG beats shows that Choi-Williams distribution is most reliable to be used for heart problem detection especially in automated systems that provide continuous monitoring for long time duration.

An RF energy harvester system using UHF micropower CMOS rectifier based on a diode connected CMOS transistor.

This paper presents a new type diode connected MOS transistor to improve CMOS conventional rectifier's performance in RF energy harvester systems for wireless sensor networks in which the circuits are designed in 0.18 µm TSMC CMOS technology. The proposed diode connected MOS transistor uses a new bulk connection which leads to reduction in the threshold voltage and leakage current; therefore, it contributes to increment of the rectifier's output voltage, output current, and efficiency when it is well important in the conventional CMOS rectifiers. The design technique for the rectifiers is explained and a matching network has been proposed to increase the sensitivity of the proposed rectifier. Five-stage rectifier with a matching network is proposed based on the optimization. The simulation results shows 18.2% improvement in the efficiency of the rectifier circuit and increase in sensitivity of RF energy harvester circuit. All circuits are designed in 0.18 µm TSMC CMOS technology.