Assessing the impact of tourist flows on emergency department treatment speed for residents and tourists. The case of Sorrento

Musella, Gaetano; Pisano, Sabrina; Scaletti, Alessandro

doi:10.1016/j.seps.2020.101004

Cited by 4 publications

(1 citation statement)

References 43 publications

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“…It is noteworthy that people and robots are equivalent: People believe, and schedules and robots effectively implement duties (Choi et al, 2020). Several other studies have recently shown that the communication between human‐robot and human‐like movements is an essential factor for healthcare professionals in the IoT sector (Agovino et al, 2021). These robots can help employees pick items or transport goods across the warehouse, referred to as collaborative robots or collaborative robots.…”

Section: Introduction To Human‐robot Interaction In the Healthcare In...mentioning

confidence: 99%

Human muscle rigidity identification by human‐robot approximation characteristics framework on internet of things platform

2021

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In the health care system and Internet of Things (IoT) platform, medical care robotics is becoming one of the quickest expanding areas of robot technology. The integration of robotics and human knowledge identifies human muscle rigidity from the healthcare data obtained from the wearable sensor. In an IoT platform, Electromyography is a method used for evaluating and tracking the electrical activity of muscles. The transferring of human muscle rigidity to a robot facilitates the robot to obtain resistive management initiatives in a useful and effective way while carrying out physical interaction activities in unstructured surroundings. The major challenges to overcome the unpredictability during physical interaction allow a robot to realize the individual behaviour with adaptability and versatility of muscles. Therefore, in this article, Human‐Robot Approximation Characteristics Framework (HRACF) has been proposed for developing physiological communication between humans and robots. HRACF permits robots to understand differential resistive abilities of muscles from human presentations. The pulses collected from Electromyography are used to retrieve human arm muscle rigidity during activity presentation. The characteristics of motion and rigidity are concurrently modelled using an estimation and approximation model with a logistic regression obtained by IoT devices. The analysed human arm muscle rigidity is then connected to the robot impedance regulator. HR model uses an optimized resistive approximator to measure the creative variables of the robot and continue driving to monitor the quoted pathways at the time of interaction. The relationship between motion data and rigidity data is systematically coded in the HR model. HRACF makes it possible to detect uncertainties through space and time that facilitates the robot to meet rigidity specification to 98[Nm/Rad] and error rate to 0.15% during physical interaction.

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Section: Introduction To Human‐robot Interaction In the Healthcare In...mentioning

confidence: 99%

Human muscle rigidity identification by human‐robot approximation characteristics framework on internet of things platform

2021

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Equilibrium and efficiency in the first aid services market: The case of the emergency department of Sorrento

Musella

Scaletti

2022

Socio-Economic Planning Sciences

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A cross-country analysis of decision-making factors influencing tourists’ shift towards circular destinations in EU-27

Alonso-Almeida,

Giglio,

Iazzolino

2024

Socio-Economic Planning Sciences

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Assessing the impact of tourist flows on emergency department treatment speed for residents and tourists. The case of Sorrento

Cited by 4 publications

References 43 publications

Human muscle rigidity identification by human‐robot approximation characteristics framework on internet of things platform

Human muscle rigidity identification by human‐robot approximation characteristics framework on internet of things platform

Equilibrium and efficiency in the first aid services market: The case of the emergency department of Sorrento

A cross-country analysis of decision-making factors influencing tourists’ shift towards circular destinations in EU-27

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