A new posture-correcting system using a vector angle model for preventing forward head posture

Yeom, Hojun; Lim, Juhun; Yoo, Sung Hak; Lee, Woo-Cheol

doi:10.1080/13102818.2014.949040

Cited by 11 publications

(8 citation statements)

References 12 publications

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“…This descriptive cross-sectional study which was approved by Sakarya University Faculty of Medicine Ethics Committee (Approval number: 71522473/050.01.04/28) was conducted in 1st and 2nd grades of medical faculty. According to Yeom et al two methods can be used to detect FHP (1).…”

Section: Methodsmentioning

confidence: 99%

“…The level of FHP is classified as slight/severe/highly FHP according to that horizontal length. The slight FHP is accepted as between 1cm-2.5cm, severe FHP between 2.5cm-5cm, and highly severe FHP 5 cm and above (1).…”

Section: Methodsmentioning

confidence: 99%

“…The rapidly increasing FHP (forward head posture) in modern society is the excessive protrusion of the neck to the anterior of the body (1). The load put on the muscles in the back and neck area increases by 0.45 kg with every 2.5 cm forward positioning of the head that may result in muscle imbalances, posture impairments and FHP which can lead to soft tissue damage, pain in the neck and scapular area, tenderness at associated sites and headaches (2).…”

Section: Introductionmentioning

confidence: 99%

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The distribution and the related factors of forward head posture among medical students

Köse

BAYLAN

KARAHAN

et al. 2022

Konuralp Tıp Dergisi

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Objective: Forward head posture (FHP) is becoming common in medical students who study for long durations with wrong postures due to intensive curriculum. This study was conducted to determine the frequency of FHP and related factors in medical students. Methods: The first and second-year medical students filled out the questionnaire including sociodemographic characteristics, activity status, Smartphone Addiction Questionnaire, Beck Depression, Body Awareness, and Perceived Stress Scales after their verbal consent was obtained. FHP and craniovertebral angle values were measured. Results: 47% of the students had highly severe (≥5 cm), 46.2% had severe FHP (2.5-5 cm), and 6.8% had mild FHP. The mean CVA (Costovertebral Angle) values were determined as 44.31 ± 4.31. The frequency of students whose CVA values are below 45° is 59.3% (140 people). The frequency of highly severe FHP was also found as high in the taller, in males, and in the students with high BMI. In the regression model examining the situations that increase the risk of severe FHP, it was found that depression increased the risk of FHP 2.5 times. Conclusions: FHP was found to be very common (90%) in medical students. FHP was found to be more severe in students with high depression scores.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The distribution and the related factors of forward head posture among medical students

Köse

BAYLAN

KARAHAN

et al. 2022

Konuralp Tıp Dergisi

View full text Add to dashboard Cite

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“…Pürkhauer et al used the Kinect ® face tracking algorithm to measure FHP [ 32 ]. Another approach is to use a combination of inertial measurement units (IMU) and strain gauges on the neck, which allows tracking the neck angle [ 33 ]. Even though these approaches seem promising, economic measurement systems are needed for reliable, valid, and objective ongoing monitoring, for example during computer work or gaming.…”

Section: Introductionmentioning

confidence: 99%

A Two Joint Neck Model to Identify Malposition of the Head Relative to the Thorax

Schmid

Bauer

Ernst

et al. 2021

Sensors

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Neck pain is a frequent health complaint. Prolonged protracted malpositions of the head are associated with neck pain and headaches and could be prevented using biofeedback systems. A practical biofeedback system to detect malpositions should be realized with a simple measurement setup. To achieve this, a simple biomechanical model representing head orientation and translation relative to the thorax is introduced. To identify the parameters of this model, anthropometric data were acquired from eight healthy volunteers. In this work we determine (i) the accuracy of the proposed model when the neck length is known, (ii) the dependency of the neck length on the body height, and (iii) the impact of a wrong neck length on the models accuracy. The resulting model is able to describe the motion of the head with a maximum uncertainty of 5 mm only. To achieve this high accuracy the effective neck length must be known a priory. If however, this parameter is assumed to be a linear function of the palpable neck length, the measurement error increases. Still, the resulting accuracy can be sufficient to identify and monitor a protracted malposition of the head relative to the thorax.

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“…Recently, as many people use smart devices in a bad posture for a long time, sit cross-legged in a chair, or sleep in the wrong posture, diseases such as turtle neck, straight neck, back pain, spinal lateral flexion, and pelvic imbalance have increased [1], [2], [3], [4]. Data from the Korea Institute of Health Insurance Review and Assessment show that 44.4% of the Korean people treated with scoliosis -spinal cord bent sideways without showing normal shape -between 2011 and 2015 are teenagers between the ages of 13 and 16 [5].…”

Section: Introductionmentioning

confidence: 99%

Assistive Devices to Help Correct Sitting-Posture Based on Posture Analysis Results

Lee

Kim

Ham

et al. 2021

JOIV : Int. J. Inform. Visualization

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As many people spend a lot of time sitting on a chair, diseases such as turtle neck, straight neck, caused by incorrect posture have been increasing. Preventing these diseases and treating initial symptoms is helpful just by sitting properly. However, when people sit, their postures become disturbed without their knowledge. In this paper, we propose an assistive device in the form of a chair that helps people to sit properly and helps correct their sitting posture. The assistive device is equipped with pressure sensors capable of measuring the distribution of pressure applied to the floor of the chair, and an ultrasonic sensor capable of measuring the distance between the user's back and the chair back. First, an ultrasonic sensor and pressure sensors are used to determine the user's posture, and if the user's posture is not correct, an alarm is sent to the user to help the user to correct the posture by himself. Second, stretching information is provided according to the degree of distribution of pressure measured by the pressure sensors, and pressures are applied to the user's back with press-type cushions to help the user sit in a correct posture. In addition, even when sitting in a chair for a long time, an alarm is triggered to induce a person to rise from the chair. After implementing the system based on Raspberry Pi, each operation was checked. Furthermore, it was confirmed through the experiment participants that the proposed assistive device can help people correct their sitting posture.

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A new posture-correcting system using a vector angle model for preventing forward head posture

Cited by 11 publications

References 12 publications

The distribution and the related factors of forward head posture among medical students

The distribution and the related factors of forward head posture among medical students

A Two Joint Neck Model to Identify Malposition of the Head Relative to the Thorax

Assistive Devices to Help Correct Sitting-Posture Based on Posture Analysis Results

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