Cyber Physical System for Stroke Detection

Laghari, Asadullah; Memon, Zulfiqar Ali; Ullah, Sadiq; Hussain, Intesab

doi:10.1109/access.2018.2851540

Cited by 22 publications

(22 citation statements)

References 43 publications

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“…The alpha waves decline when the CBF decreases. The theta and delta waves appear when the CBF further decreases [ 91 , 92 , 93 ]. Besides the sub bands analysis of EEG, the local brain symmetry index (BSI), relevant delta power, and relative local delta to alpha ratio (DAR) calculated from the recorded EEG signals are used as indices for detecting stroke.…”

Section: Wearable Devices For Stroke Risk Predictionmentioning

confidence: 99%

Trends and Challenges of Wearable Multimodal Technologies for Stroke Risk Prediction

Chen

2021

Sensors

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We review in this paper the wearable-based technologies intended for real-time monitoring of stroke-related physiological parameters. These measurements are undertaken to prevent death and disability due to stroke. We compare the various characteristics, such as weight, accessibility, frequency of use, data continuity, and response time of these wearables. It was found that the most user-friendly wearables can have limitations in reporting high-precision prediction outcomes. Therefore, we report also the trend of integrating these wearables into the internet of things (IoT) and combining electronic health records (EHRs) and machine learning (ML) algorithms to establish a stroke risk prediction system. Due to different characteristics, such as accessibility, time, and spatial resolution of various wearable-based technologies, strategies of applying different types of wearables to maximize the efficacy of stroke risk prediction are also reported. In addition, based on the various applications of multimodal electroencephalography–functional near-infrared spectroscopy (EEG–fNIRS) on stroke patients, the perspective of using this technique to improve the prediction performance is elaborated. Expected prediction has to be dynamically delivered with high-precision outcomes. There is a need for stroke risk stratification and management to reduce the resulting social and economic burden.

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Section: Wearable Devices For Stroke Risk Predictionmentioning

confidence: 99%

Trends and Challenges of Wearable Multimodal Technologies for Stroke Risk Prediction

Chen

2021

Sensors

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“…3), higher the priority level, larger the value. In the proposed work, two different types of value are used, linear and nonlinear (see details in Table II) to support different QoS requirements of data packet based on the important/ emergency levels [9][10][11]. In this mechanism, if a sender has data to send, it kickoffs the process by setting its txRetries value to maxTxRetries.…”

Section: A Csma P-persistent Mechanism With Varied By Priority Levelmentioning

confidence: 99%

“…NDUSTRIAL wireless sensor network (IWSN) can be defined as a network of sensors which gathers information from monitored areas using wireless links. The ease of deployment and the potential for scalability/flexibility of IWSNs have resulted in its wider adaptation [1][2][3][4] such as automation, process control, health industry and environmental monitoring [5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

“…In IWSNs, in accordance with the emergency levels or criticality of applications, various priority levels can be established [10]. In healthcare, higher priority levels are mostly assigned to emergency events such as first aid for stroke patients [9], or accidents [11]. In other industries, events such as fire hazards, leakages, sensory readings exceeding critical thresholds, poisonous gas or liquid detection in chemical industry [7] can be classified as emergency.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Delay and Reliability Analysis of p-Persistent Carrier Sense Multiple Access for Multi-Event Industrial Wireless Sensor Networks

Nguyen¹,

Trinh²,

Ban³

et al. 2020

IEEE Sensors J.

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“…These drawbacks justify the seek for a novelty in the field of model design for industrial machines. The new technique sights for CPSs with Real-Time performance modelled at the system engineering level and capable of enough fidelity for virtual commissioning [17]- [20]. It brings new benefits in the field of model design for industrial machines, as the set of equations defining the CPS are based on data-sheet information rather than complex physical properties.…”

Section: Introductionmentioning

confidence: 99%

A Methodology for Real-Time HiL Validation of Hydraulic-Press Controllers Based on Novel Modeling Techniques

et al. 2019

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Industrial machines commissioning consumes a great amount of man-hours, due to control designers lack of knowledge about the final controller gains before they start working with it. Virtual commissioning has been postulated as an optimal solution to deal with this lack of knowledge when the Real-Time simulation of the digital models reproduces an identical behaviour as the industrial machines they represent. Cyber-Physical Systems (CPSs) offer new opportunities in this field, however, in the case of industrial machines, acquiring this level of accuracy requires to slow down the simulation. On this paper, novel modelling techniques for industrial CPSs have been presented. They are introduced to help in the evolution from conventional control design to a virtual commissioning process combining software and hardware capabilities. This methodology has been tested with a hydraulic-press model designed following manufacturer specifications, initially under a Software in the Loop (SiL) validation platform and, afterwards, in a Hardware in the Loop (HiL) validation platform. The control algorithms are designed in laboratory conditions harmless for the machine, embedding them later in the industrial environment without further modifications. INDEX TERMS Electrohydraulics, hydraulic systems, real time systems, system-level design, virtual manufacturing.

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Cyber Physical System for Stroke Detection

Cited by 22 publications

References 43 publications

Trends and Challenges of Wearable Multimodal Technologies for Stroke Risk Prediction

Trends and Challenges of Wearable Multimodal Technologies for Stroke Risk Prediction

Delay and Reliability Analysis of p-Persistent Carrier Sense Multiple Access for Multi-Event Industrial Wireless Sensor Networks

A Methodology for Real-Time HiL Validation of Hydraulic-Press Controllers Based on Novel Modeling Techniques

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