Maziar Hosseinzadeh’s research while affiliated with Islamic Azad University, Isfahan and other places

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Publications (1)


Figure 1: The main practical factors influencing resting quality [1,4,5]
Figure 2: Schematic of the body parts. Area 1 is the head and neck (occipital muscle), Area 2 is the shoulders (rhomboid major muscles), and Area 3 is the lumbar spine (spine endpoint)
Figure 3: Schematic of the ergonomic mattress and pillow detection device. The temperature, force, and humidity were as the input and the PC section was as the output to display the results
Figure 5: Multitasking processing diagram
Figure 6: The initial temperature sensor board arrangement and the Arduino processor

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Recognition System for Ergonomic Mattress and Pillow: Design and Fabrication
  • Article
  • Full-text available

January 2023

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682 Reads

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15 Citations

IETE Journal of Research

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Maziar Hosseinzadeh

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Bhagyashree P. Joshi

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Getting proper rest is an essential issue, but it is neglected as the major component of every person’s overall health and well-being. Enough proper rest has a lot of proven health benefits. This paper aims at proposing a systematic framework to find the suitable pillows and mattresses for individuals to have proper rest and sleep. The proposed system includes a set of force-sensing resistors (FSR), thermal sensors, humidity-thermal sensors, and a central unit to process the acquired data. Customized software in LabVIEW is developed to monitor the results and ultimately identify the proper ergonomic mattresses and pillows for users. Initial experiments were performed based on zonal performance and multitasking to design, construct, and test each system as a novel hypothesis. The studies and tests were carried out in two steps. The first step included hardware testing and sensor arrangement, and the second step involved processing the acquired data to identify a good product. In this study, we propose a feasible framework to select convenient mattresses and pillows for each person.

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Citations (1)


... In response to the shortcomings of existing flat armchairs, Nooraziah et al. [17] used a combination of neural networks and MLR (Multiple Linear Regression) for predictive analysis in 2024 and successfully developed a new ergonomic chair. Although such research [18,19] has made some progress, most solutions rely on static sitting data and fail to fully consider the human body's posture changes and individual differences in an active state [20,21]. Researchers such as Math [22] and Ahmed [23] tried to optimize seat design by combining traditional mechanical models, but their methods still have certain limitations and cannot meet the needs of different patients in different situations [24]. ...

Reference:

Application of biomechanics in graphic design and ergonomic optimization
Recognition System for Ergonomic Mattress and Pillow: Design and Fabrication

IETE Journal of Research