Thermal effects of mobile phones on human auricle region

2018 · Mixed · Low evidence

← Research stream

MixedLow evidencePaper 1958

Study snapshot

Publicationmanual · 2018

Study typeengineering

Reported directionMixed

Evidence ratingLow

Abstract

Thermal effects of mobile phones on human auricle region Bauer J, O'Mahony C, Drahomir Chovan, John Mulcahy, Christophe Silien and Syed A.M. Tofail. Thermal effects of mobile phones on human auricle region. Journal of Thermal Biology. doi.org Highlights • An in silico model of thermal heating of human auricle region due to mobile phone has been developed from first principle and using a COMSOL Multiphysics • The model allowed determination of the impact of battery discharge rate, battery capacity, battery cathode material, biological tissue distance, antenna radio-wave frequency and intensity. • Mobile phone heating during a typical call has been simulated and compared with experimental infrared thermographic imaging. • 1800MHz frequency of data transmission showed the highest temperature increase in the fat/water phantom • Heating process is generally dominated by the CPU heat although antenna heat can penetrate deeper and can still be a cause of concern. • The proposed model can be used for the understanding of negative mobile phones impact on human health, including prediction and comprehension of eventual long and short-term side effects • This new model will aid designing of mobile phones to prevent causing potential negative thermal effect. Abstract Mobile phones have become an indispensable utility to modern society, with international use increasing dramatically each year. The GSM signal operates at 900 MHz, 1800MHz and 2250 MHz, may potentially cause harm to human tissue. Yet there is no in silico model to aid design these devices to protect from causing potential thermal effect. Here we present a model of sources of heating in a mobile phone device with experimental verification during the phone call. We have developed this mobile phone thermal model using first principles on COMSOL(r) Multiphysics modelling platform to simulate heating effect in human auricle region due to mobile phone use. In particular, our model considered both radiative and non-radiative heating from components such as the lithium ion battery, CPU circuitry and the antenna. The model showed the distribution and effect of the heating effect due to mobile phone use and considered impact of battery discharge rate, battery capacity, battery cathode material, biological tissue distance, antenna radio-wave frequency and intensity. Furthermore, the lithium ion battery heating was validated during experiments using temperature sensors with an excellent agreement between simulated and experimental data (<1% variation). Mobile phone heating during a typical call has also been simulated and compared with experimental infrared thermographic imaging. Importantly, we found that 1800MHz frequency of data transmission showed the highest temperature increase in the fat/water phantom used in this simulation. We also successfully compared heating distribution in human auricle region during mobile phone use with clinical thermographic images with reasonable qualitative and quantitative agreements. In summary, our model provides a foundation to conceive thermal and other physical effects caused by mobile phone use and allow for the understanding of potential negative health effects thus supporting and promoting personalized and preventive medicine using thermography. Excerpt For the frequencies active in mobile phones, 900MHz, 1800MHz and 2250MHz, 1800MHz showed the highest temperature increase in the fat/water phantom used in this simulation. 900MHz and 2250MHz showed similar heating, but below 1 degree C. Varying the distance of the complete mobile phone model from the phantom cube, the temperature increased by a factor of 10 from contact with the phantom compared to 50 mm away. The model shows that the temperature was dominated by the CPU heat, conduction from and exceeded the contributions to the heating from the antenna and the battery. The antenna heat, however, has more penetrative properties. This allowed for temperature changes to travel deeper and cause much serious temperature effect on soft tissues and brain. sciencedirect.com

Machine Enhanced Logic

AI evidence extraction

Structured fields below were generated from the paper’s abstract and metadata to make the evidence easier to inspect. Automated extraction may be incomplete or incorrect; verify important details against the original paper.

Study typeengineering

Effect directionmixed

PopulationNot supplied

Sample sizeNot supplied

ExposureRF · typical call (simulated)

Evidence strengthLowConfidence: 74% · Peer reviewed: yes

Main findings

An in silico COMSOL model of mobile phone-related heating in the human auricle region was developed and compared with experimental temperature sensor data for battery heating (<1% variation) and with infrared thermographic imaging during a typical call. In simulations, 1800 MHz showed the highest temperature increase in a fat/water phantom; 900 MHz and 2250 MHz showed similar heating reported as below 1°C. The model indicated heating was generally dominated by CPU heat, while antenna-related heating was described as more penetrative.

Outcomes measured

Temperature increase/heating in human auricle region
Thermal distribution in tissue/phantom during mobile phone use
Comparison of simulated heating with infrared thermographic imaging
Battery heating validation vs temperature sensors

Limitations

Primarily an in silico/engineering modeling study with experimental verification focused on thermal measurements rather than clinical health outcomes
Use of a fat/water phantom and thermographic comparisons may not fully represent in vivo human tissue conditions
Quantitative exposure metrics (e.g., SAR, field strength/intensity values) are not provided in the abstract

View raw extracted JSON

{
  "study_type": "engineering",
  "exposure": {
    "band": "RF",
    "source": "mobile phone",
    "frequency_mhz": null,
    "sar_wkg": null,
    "duration": "typical call (simulated)"
  },
  "population": null,
  "sample_size": null,
  "outcomes": [
    "Temperature increase/heating in human auricle region",
    "Thermal distribution in tissue/phantom during mobile phone use",
    "Comparison of simulated heating with infrared thermographic imaging",
    "Battery heating validation vs temperature sensors"
  ],
  "main_findings": "An in silico COMSOL model of mobile phone-related heating in the human auricle region was developed and compared with experimental temperature sensor data for battery heating (<1% variation) and with infrared thermographic imaging during a typical call. In simulations, 1800 MHz showed the highest temperature increase in a fat/water phantom; 900 MHz and 2250 MHz showed similar heating reported as below 1°C. The model indicated heating was generally dominated by CPU heat, while antenna-related heating was described as more penetrative.",
  "effect_direction": "mixed",
  "limitations": [
    "Primarily an in silico/engineering modeling study with experimental verification focused on thermal measurements rather than clinical health outcomes",
    "Use of a fat/water phantom and thermographic comparisons may not fully represent in vivo human tissue conditions",
    "Quantitative exposure metrics (e.g., SAR, field strength/intensity values) are not provided in the abstract"
  ],
  "evidence_strength": "low",
  "confidence": 0.74,
  "peer_reviewed_likely": "yes",
  "keywords": [
    "mobile phone",
    "GSM",
    "RF",
    "900 MHz",
    "1800 MHz",
    "2250 MHz",
    "thermal effects",
    "auricle",
    "COMSOL Multiphysics",
    "infrared thermography",
    "phantom",
    "battery heating",
    "CPU heat",
    "antenna"
  ],
  "suggested_hubs": []
}

AI can be wrong. Always verify against the paper.

AI-extracted fields are generated from the abstract and metadata and may be incomplete or incorrect. This material is for informational purposes and is not medical advice.

Identifiers and source

DOI: 10.1016/j.jtherbio.2018.11.008
PubMed: Not supplied

Read the original paper →

Related papers

← Back to the Research Library