Industry 4.0 Technologies in Maternal Healthcare: A Systematic

Asri (2021) proposed the use of Databricks platform together with Spark to analyze data for real-time forecasting. They are useful in analyzing the shape of the objects in the drone's field of view.

Rest API

As the second step in the ETA calculation system, it runs support vector regression on each cluster to predict the ETA value for a given sample. Since it runs on a selected cluster, it gives more accurate results than running support vector regression on the full data set.

RESULT AND DISCUSSION A. Prescription handling and Logistic Management

The system divides the dataset into 3 groups because according to the Elbow method it was the best number of clusters into which the dataset can be divided.

This application helps users to predict more accurate ETA value than mathematically calculated ETA value.

Autonomous drone navigation and obstacles avoidance The autonomous navigation of the drone uses GPS

CONCLUSION

The proposed system includes body condition monitoring strategies for fever, pulse oximetry, and heart rate. Depending on the force of the fall, the static or dynamic state of the person and the connected sensor unit, the data exceeds the normal value and the falling machine receives the signal in which the system sends an automatic notification.

Keywords-Temperature, Pulse oximetry, heart rate, receiving fall, IOT

INTRODUCTION
EXISTING SYSTEM
ARDUINO UNO
HEARTBEAT SENSOR
LCD DISPLAY
TEMPERATURE SENSOR
RESISTIVE TEMPERATURE DEVICE

RESULTS
CONCLUSION

The rhythm of the heart and the heartbeat that can be felt in any artery that is close to the pulse. It supports the change of resistance throughout the semiconductor and the resistance decreases non-linearly with increasing temperature.

ScienceDirect

Abstract

Introduction
Literature Review
Suggestive Model

Cases

Cardiovascular disorder (CVD)
Patient is identified with Cardiovascular disorder (CVD)
Patient gets registered for CVD in the nearby health centre
FOG layer detects the CVD entry and recommends mandatory processes and nearby pathological laboratories with contact information for making decisions regarding the calculation of a patient’s health risk and to reduce latency
Patient is admitted to the nearest/appropriate health centre for suggested surgery
Feasibility of Tele-surgery is evaluated on the basis of initial pre-operative tests and technology support for the Tele-surgery at the health centre
The operator room is set up in the hospital of a remote area and specialized surgeon who is in another city or country will perform the partition of the cystic duct artery and cholecystectomy while induction of pneumoperitoneum
Three apertures are made on the body of the patient after he has been anaesthetised, to allow the rode to enter
Recovery rate and post-operative complications of patient decides the course of support be assisted to patient Step11: Post-operative measures to be monitored at FOG Layer with expert medical support are
Once the patient returns to the normal routine, usually within five days of surgery, the only concern will be the wound due to incision, pain medication will be probably prescribed by a doctor before leaving the hospital
Regular monitoring and tests would be recommended, the readings obtained are compared to standards
Cataract surgery
Patient is identified with Cataract
Patient gets registered for cataract surgery in nearby health centre
FOG layer detects the cataract surgery entry and recommends mandatory processes and nearby pathological laboratories with contact information for making decisions regarding the calculation of a patient’s health risk and to
The operator room is set up in hospital of a remote area and specialized surgeon who is another city will perform the dissection of the cystic duct artery and cholecystectomy while induction of pneumoperitoneum and robot
Regular monitoring and tests would be recommended, the readings obtained will be compared with the standards. Discrepancies if any would be directed to health centres with immediate support being handled by the FOG

Oncologic surgery 2002 Surgeon’s performed tele-surgery for colon cancer, esophageal tumors, gastric cancer, retromediastinal tumors and thymoma on patients of remote area
Nissen fundoplication (surgery to treat chronic
Urlogic surgery 2004 The most common operation performed through robots and are gaining widespread recognition in the United States and Europe is radical robotic prostatectomy
Cardiothoracic surgery 2005 Cardiothoracic surgeons can perform complex cardiothoracic procedures while avoiding the significant morbidity of thoracotomy and sternotomy. Hundreds of
Televascular surgery 2015 NASA conducted experiments in this area like abdominal surgery and laparoscopic cholecystectomy for astronaut
Teleneurosurgery 2015 Trans-sphenoidal resection of a pituitary tumor with 10 msec of latency time was presented by Wirz et al
Challenges and Issues
Conclusion

Robotic arms receive the control commands from the surgeon's console and perform the surgical process on the patient's body. At the same time, the tactile feedback data from the patient is sent to the surgeon's console which is sensed by the tactile perception device.

2005) “Creating the world's first remote telerobotic surgical service: for providing advanced laparoscopic surgery in a rural community”. 2006) "Telemedicine and Collaborative Health Information Systems (Telemedizin und Kollaborative Gesundheitsinformationssysteme)." IT-Information Technology Telemedicine: barriers and opportunities in the 21st century.

APJCP 18(10): 2775

Methods

Papers from the selected studies were collected after identifying the research questions. After searching, the number of papers per search strategy or topic indicated in fig.

Research Questions

Public dataset i. DEAP and SEED

In edge computing, data processing is done in the edge layer instead of the cloud layer. In [27] and [28], the authors proposed a similar network structure for edge computing in healthcare to reduce the total cost of the system. In addition, it highlighted intelligent decision-making systems and the use of the panorama decision-making framework in the third category.

The result showed an improvement in the efficiency of the proposed fusion method compared to other current fusion approaches. Objective: This paper systematically reviews emerging information technologies for data modeling and analytics that have the potential to achieve Data Centric Healthcare (DCHC) for the envisioned goal of sustainable healthcare. The purpose of this review is to: 1) identify new information technologies with potential for data modeling and analytics, and 2) explore recent research of these technologies at DCHC. This paper examines new information technologies for Data-Centric Healthcare (DCHC) that will support sustainable healthcare. The objectives of this review are to: 1) identify emerging information technologies with potential for data modeling and analytics and 2) explore recent research on these technologies.

Methodology

New information technologies such as Virtual Reality (VR), Augmented Reality (AR), Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Digital Twin (DT), Internet of Things (IoT) and Big Data (BD ) have proven effective for data modeling and predictive analytics in others. This paper reviews emerging information technologies for Data-Centric Health-Care (DCHC) that will support sustainable healthcare. The purpose of this review is to: 1) identify new information technologies with potential for data modeling and analysis, and 2) explore recent research on these technologies.

This is a gap in the literature as we could not find any publication investigating the topic of this review paper. Our approach for this review can be evaluated by comparison with the procedure proposed by Okoli [8]. Section 5 provides conclusions regarding the future direction of research for an envisioned sustainable predictive universal digital health ecosystem based on the findings of the review and analysis.

Emerging information technologies for DCHC

64] • Proposed a real-time analytical approach based on seamlessly collected sensory data to monitor patients' vital signs. 67] •Proposed “DeepReco”, an Intelligent Health Recommender System (HRS) based on Restricted Boltzmann Machine-Convolutional Neural Network (RBM-CNN, DL method). 76] •Proposed a risk prediction model based on administrative data and ML techniques to determine CVD risk in patients with type 2 diabetes.

103] •Proposed “T-CPS”, an energy-aware cyber-physical therapy system assisted by big data analytics and cloud-oriented. 78] •Proposed “CloudDTH”, a cloud-based digital twin healthcare system to monitor, diagnose and predict various health aspects of an individual. 83] • Proposed DT Frameworks (Better Community Healthcare, Intelligent Control and Emergency Planning in Hospitals, Strategic Planning of Hospital Services) for precision healthcare.

Synthesis and extraction of research thematic

Interaction and Convergence: DT ensures existence and co-involvement in the physical object's full life cycle. It is therefore understood that the definition of Big Data is subject to technological progress [87]. Research of VR and AR technologies in the reviewed research found a focus on elderly care and rehabilitation; for assistance, monitoring (visualization) and analysis.

The concept of data centralization was first perceived and actualized in the early 1990s, through the introduction of EHRs. In the architecture, the user holds a high-resolution stereoscopic display and a haptic stylus on top of the display, which provides a highly realistic surgical simulation. The viewer can be calibrated depending on the users and can illustrate high-quality 3D images on the visual surface.

Concluding remarks

Conceptual The system was tested with a dataset of 250 coronary angiography studies (each containing more than 3000 images). Conceptual The system was tested with RCT data and data (from trained ML models) and demonstrated efficacy (85% accuracy). An innovative and effective robotics method to assist Parkinson's patients using IoT in big data analytics.

Zhang, et al., The impact of population aging on medical expenditures: a big data study based on the life table, Biosci. L'opez-Coronado, A systematic review of techniques and sources of big data in the health care sector, Med. Czard, Toward a Literature-Driven Definition of Big Data in Healthcare [Research Article], 2015, https://doi.org/10.1155/.

I NTRODUCTION

Abstract — The focus of the new era of healthcare is the Medical Internet of Things in relation to prevention and prediction (p2Health). In addition, the doctor, as a patient observer, has the possibility to set the required measurement parameters via the IoT gateway and activate/deactivate the sensors on the wearable devices in real time. Therefore, according to the target investigation, patients' status, demands and requirements, doctors can determine the setting parameters for the measurement.

Several types of research have reported a negative effect of ambient pollutants on health status and especially on patients suffering from physiological parameters and vital signs [12]-[14]. However, simultaneous monitoring of the ambient and physiological parameters, synchronization of data and study of the interaction is a step forward to investigate the effect of each parameter on the other and specify the weight of the effect. Parameter monitoring of wearables and application, adjustment of sampling rates, synchronization and implementation.

RELATED WORKS

Ambient Parameters Monitoring

Physiological Indicators Platforms

CO, NO, O3, temp., humid-

Ambient-Physiological Monitoring Platforms
Dieffendefer et al. introduced a hybrid low-power system for environmental and physiological parameters monitoring
Gardaˇsevi´c et. al [50] proposed a preliminary framework for physiological and ambient parameter monitoring in IoT

C ONCEPT AND S TRUCTURE

Requirements and Contributions

Wearability: It was discussed earlier that preventive medicine requires continuous and comprehensive data mon-
Multi-Parameters Monitoring: To reach a comprehen- sive monitoring in healthcare, a pervasive monitoring in ambi-

Although the presented systems are not fully covered (only physiological parameters), they describe the combination of environmental and physiological parameters monitoring. A summary of the works presented in the previous two subsections is given in Table II. Toxic/hazardous gases, noise, UV, air temperature, humidity and pressure are included in the scope of personalized environmental monitoring.

Especially in field studies aimed at measuring authentic data in the daily environment, the measurement setting minimizes the influence on the users. Ubiqsense was developed as a wrist-worn prototype to meet these environmental monitoring requirements. To achieve comprehensive monitoring in healthcare, in-depth monitoring in ambitious monitoring in healthcare, in-depth monitoring in ambitious monitoring.

EEG, ECG, EMG (eye

Adaptability: The bandwidth of investigation scenarios in the field of preventive and occupational monitoring re-
Configurability: Beside the adaptability, the opportunity of performing an investigation, planning from higher level
Data Integration: The integration of such data includes intra-inter-individual parameters and sensors aspects, which
Data Source Accessibility

Directly-accessible data sources: These sensors use open communication protocols and allow the connection by
Indirectly-accessible data sources: These sources use closed communication specifications and forward the data

Structure and Architecture Description

Data Management Level: The highest level consists of the involved cloud-solutions, with the system internal
Data Collection Level: The second level bases on per- sonal mobile devices (smartphones), which function as IoT-
Sensor Node Level: The third level includes the different WBAN-related sensor-nodes worn by the user (individual)
PHYSICAL AND PHYSIOLOGICAL PARAMETERS MONITORING
ENVIRONMENTAL PARAMETERS MONITORING: UBIQSENSE

Structure and Engineering of Ubiqsense
Hardware Design: Physical Layers Description

Host platform: including microcontroller unit, data transmission, and integrated sensors: The main platform as
Top layer: gas sensor node: In order to detect toxic and hazardous gases, the gas sensor is located at the top of
Bottom layer: Battery holder: In personalized healthcare monitoring, convenient and prolonged monitoring are in high
Linking layer: hardware interface: It is the heart of this approach that links the add-on sensors (gas sensor node, noise,
Notification layer: abnormal status warner: The user warning is an essential feature in safety monitoring devices

Architecture and Operational Strategy of Ubiqsense Data acquisition and protection for further analysis as the

Channel between Ubiqsense and gateway is established
Channel between Ubiqsense and gateway is discon- nected: In BLE disconnected mode, Ubiqsense operates in

Environmental Sensors

Add-on Sensors: Gas, noise, and UV are add-on sensors
Integrated Sensors: Air pressure, air humidity, and tem- perature are integrated and distributed on both sides of the

Design and Implementation: Software
MCU-sensors Communication Mode
Data Transmission to IoT Gateway

INFORMATION MANAGEMENT AND COMMUNICATION
D ISCUSSION : A PPLICATION AND R ESULTS
C ONCLUSION AND F UTURE W ORK

This includes the connection to the required sensor nodes (directly accessible data sources) and external cloud solutions (indirectly accessible data sources), the data collection and preparation as well as the provision of data for the p2Health Cloud in accordance with the instructions of the measurement tasks. The top and bottom of the hardware interface are connected to the guest sensor node and the host platform, respectively. Therefore, the data from Ubiqsense is transferred to the smartphone in 5 different packets via BLE.

For example, basic functions of the p2Health Cloud related to data processing are delegated to the IoT gateway. Communication with the cloud solutions (Fitbit, Nokia or Garmin) and with the p2Health Cloud is based on an API (Application Programming Interface). Due to space limitations, only a small portion of the collected data is presented here.

A PPENDIXES

R EFERENCES

Research objectives and their medical conditions 1. Purpose of research

Sources of medical information
Epidemiological interview

Has the patient been in COVID-19 infected areas for 14 days;
Has he / she been in close contact with people from virus-infected areas in the last 14 days;
Did he maintain contacts with people whose infection was confirmed by a laboratory

Clinical symptoms
Laboratory diagnosis
Instrumental diagnostics
Post-disease complications

Functional architecture of the Platform 1. Functional components
Functional monitoring;
Obtaining historical data;
Medical interviews;
Local and mobile diagnostics;
Knowledge databases;
A specialist office

Functional monitoring
Historical medical data acquisition system
Local interview system
Local and Mobile diagnostic system
Knowledge database
A specialist office

Architecture of the Intelligent Platform – AI to the rescue

It is designed to collect information about the patient's basic vital signs during daily activities. It is designed to collect information about the patient's basic vital signs during daily activities. The basic information sources used in the operation of the system are shown in Fig. 1.

With an unclear location of the inflammatory process, the radiograph is shown in the right lateral projection [11]. With an unclear location of the inflammatory process, the radiograph is shown in the right lateral projection [11]. Special attention has been paid to the use of diagnostic imaging results (X-ray, Computed Tomography, Magnetic Resonance, Ultrasonographic Examinations).

Current progress of the work
Related Works
Methodology

Hardware Description
Data-set Description
Preprocessing
Feature Extraction 1. Wavelet energy
Classification
Fall Recognition 1. Data Acquisition

Post classification
Results and Discussion
Conclusion
Domain overview
MedPlus applications

Data source
Collected Data
Digitization of medical records
Data analysis
Patient profile

System evaluation

Methodology

Visualize statistics for collected health data synced through Google Fit Visualize the patients list
Look after detected anomalies in the last 7 days Visualize the profile of each patient (statistics, detected anomalies, electronic medical records, last symptoms, diagnosis history)
Introduce symptom by vocal command in both Romanian and English Introduce diagnosis for their patients 7. Receive diagnosis from assigned doctor
Upload medical records

Results
Remarks

The user interfaces look very attractive and were appreciated positive both by doctors and nurses and by patients;
Even in the few cases where functionality was a bit hard to digest for someone outside the field, after explanations and after given examples, things became more clear;
The devices presented great performance and stability;
All participants agree that the data collection and interpretation are quite attractive and it can help patients to be monitored remotely;
Also, automatic assessment and identification of abnormalities help patients (who are treated immediately and reach this state), but also doctors (who immediately receive the results of processing huge amounts of data)

In specific cases, the size of the system (i.e. the number of active users) will determine the choice of solution. In practice, however, the effectiveness of the platform depends on the amount of data processed: the more data, the more accurate the results. The massive use of the platform, especially in the field of data acquisition, should be considered the key to its success.

Due to the large distribution of the health services, it is necessary to design the Platform properly. The functioning of the platform can also be modified from the point of view of the sources of information used about the patient's health. In the second extreme case, diagnosis and therapy will be determined only on the basis of the doctor's knowledge.