Implementation of wheelchair controller using mouth and tongue gesture

Hassani, Rafia; Boumehraz, Mohamed; Hamzi, Maroua

doi:10.11591/ijeecs.v24.i3.pp1663-1671

Cited by 2 publications

(2 citation statements)

References 21 publications

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“…In general, the HMI is widely used in industrial sectors involved in process control of the plant by using the programmable logic controller [22]. Nowadays, the HMI included a graphical user interface (GUI) could apply to smart home, smart agriculture, and smart equipment [23], [24]. The authors' intention was to design for users' friendly access with this device as Figure 4.…”

Section: Human Machine Interface Modulementioning

confidence: 99%

Design and realization of a dual-wavelength low level light therapy for acne and face rejuvenation treatment

Watjanatepin

Kiatsookkanatorn

Boonmee

et al. 2022

IJEECS

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Low-level light therapy (LLLT) uses the light of wavelength between 400–700 nm to treat acne, reduce inflammation, stimulate collagen production, and rejuvenate the facial skin. This study designed and constructed a dual-wavelength LED LLLT device for the facial treatment. The light spectrum, power density, uniformity, stability, and safety of the device were analyzed. The proposed system consisted of an LED array with 415 and 633 nm wavelengths. Human machine interface with embedded system was used to control light intensity and treatment time. The phototherapy device is designed to be curvaceously sized to suit the face shape of Asian people. The results showed that the LLLT device emitted 633±5 nm red and 415±5 nm blue light with a linear adjustable light power density of 0-18.56 mW/cm2 and 0-3.70 mW/cm2, respectively. The spectrum distribution of the red and blue light was relatively constant over 30 minutes of operation. The uniformity and stability of red spectrum were about 89.9% and 95.08% and blue spectrum were 87.6% and 97.08%, respectively. The experimental face’s temperature was below 31.5 . For the future study, the LED phototherapy device will be applied for clinical research in collaboration with dermatologists.Low-level light therapy (LLLT) uses the light of wavelength between 400–700 nm to treat acne, reduce inflammation, stimulate collagen production, and rejuvenate the facial skin. This study designed and constructed a dual-wavelength LED LLLT device for the facial treatment. The light spectrum, power density, uniformity, stability, and safety of the device were analyzed. The proposed system consisted of an LED array with 415 and 633 nm wavelengths. Human machine interface with embedded system was used to control light intensity and treatment time. The phototherapy device is designed to be curvaceously sized to suit the face shape of Asian people. The results showed that the LLLT device emitted 633±5 nm red and 415±5 nm blue light with a linear adjustable light power density of 0-18.56 mW/cm2 and 0-3.70 mW/cm2, respectively. The spectrum distribution of the red and blue light was relatively constant over 30 minutes of operation. The uniformity and stability of red spectrum were about 89.9% and 95.08% and blue spectrum were 87.6% and 97.08%, respectively. The experimental face’s temperature was below 31.5 . For the future study, the LED phototherapy device will be applied for clinical research in collaboration with dermatologists.

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Section: Human Machine Interface Modulementioning

confidence: 99%

Design and realization of a dual-wavelength low level light therapy for acne and face rejuvenation treatment

Watjanatepin

Kiatsookkanatorn

Boonmee

et al. 2022

IJEECS

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“…In recent years, smart wheelchair systems have been developed to assist people with disabilities [1]- [3]. Researches often focuses on three main areas: i) improvement of assistive technology; ii) improving physical user interface; and iii) improving control sharing between user and machine.…”

Section: Introductionmentioning

confidence: 99%

Positioning an electric wheelchair in 2D grid map based on natural landmarks for navigation using Q-learning

Ngo

Hải

2023

IJEECS

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Self-mobility electric wheelchairs are very useful for people with disabilities, so they can move without help in indoor environments. To create one selfmobility electric wheelchair, modern methods for control such as computer vision and machine learning can be applied. In particular, this electric wheelchair can move from any position in the indoor environment to the desired destination. For accuracy, natural landmarks are used and the navigation of the wheelchair is determined using a Q-learning reinforcement learning algorithm. In particular, this algorithm is applied to find the best path for the wheelchair to reach the destination. The article proposes a method to build one 2D grid map for wheelchair movement based on natural landmarks in the indoor environment. The new point of this method is that the position of the wheelchair can be accurately determined from a certain landmark instead of many landmarks applied in traditional methods. Some practical experiments were performed to illustrate the effectiveness of the proposed method in the indoor environment. This proposed method can be developed in more complex environments with natural landmarks.

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Implementation of wheelchair controller using mouth and tongue gesture

Cited by 2 publications

References 21 publications

Design and realization of a dual-wavelength low level light therapy for acne and face rejuvenation treatment

Design and realization of a dual-wavelength low level light therapy for acne and face rejuvenation treatment

Positioning an electric wheelchair in 2D grid map based on natural landmarks for navigation using Q-learning

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