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An innovative technical solution to avoid Insomnia and Noise-Induced Hearing Loss

Shriram KV

Shriram KV

Bengaluru, Karnataka

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  • 0 Collaborators

: The major challenge these days with the increased usage of the mobile phone is loss of sleep (insomnia), increased stress and finally more damages to the health and mental wellness. Most of us have the habit of even keeping the phone underneath the pillow while sleeping. There are people who are now treated for mobile addiction. People are there to use phone to get sleep sooner. Sleep time is meant for the brain to rejuvenate, organise thoughts and relax. If the sleep patterns are disturbed due to a continuous external commotion, it will result in the subconscious to spend energy and brain space. Hence, it is wise to switch off the music after the person sleeps which most of us do not do as we are already slept by then. Also, wearing headphones for an hour will increase the bacteria in your ears by 700 times. Many researches in the past prove that music is a solution to reduce stress and to bring sleep. But, we, the users are using headphones for music and it causes some dangerous side effects including affecting the sleep and noise induced hearing loss. There is a strong need to avoid unnecessary health problems which are meant to be avoided. Here, we propose a system which will ensure that the music player is stopped after understanding that the person using it has slept and he no more needs the tunes there by not disturbing the deep sleep and preventing insomnia and noise induced hearing loss. Novelty is what we present in this research through making sure if the person has really slept or not. Our innovative system switches off the audio automatically when a person falls asleep. The same can be expanded and improvised to provide analytics to the user as in how many hours did he sleep peacefully, how is his body tuned towards listening to music, how long does he need music, under what conditions does he over listen or under listen etc. ...learn more

Project status: Published/In Market

Internet of Things, Artificial Intelligence

Code Samples [1]

Overview / Usage

One would be surprised to know the following statistics about Insomnia (sleeplessness), which will make the readers’, understand the impact of having bad sleep or sleeplessness.

• The sleep rate of the people has been reduced by 20%, reports say.

• A shocking statistics about insomnia says that 30% of the people have this.
• To make this data a matter of concern, it is confirmed that one in three has insomnia.
• Insomnia definitely leads to stress and further complications related to stress.
• Women have more chance to be affected by Insomnia, reports claim.

• 90% of the people who have stress-related illness report that they feel insomnia as well.

• Many of the insomnia patients seek medical help and aid, which has side effects, even doctors say.
• People who suffer from insomnia have the risk of gaining overweight.

The simple solution that many follow is to listen to music with headphones to bring sleep. Many people listen to music to improve their sleep, but the effect of listening to music is unclear. Here, when headphones are used there are following risks which are never exposed much:

After gaining sleep, still the headphones are connected and music will keep playing. This will even distract sleep in between leading to sleeplessness causing Insomnia again. The method used to avoid Insomnia may induce Insomnia again.

Usage of headphones during sleep may cause Noise-Induced Hearing Loss, which is further dangerous. We have built a system which would understand that the person has slept and will stop the music being played, real time. This would reduce the chances of getting Insomnia.

Methodology / Approach

Our proposed system shall comprise the following:

  1. A wearable device (Fitbit) which helps in acquiring the real-time sleep data.

  2. An app built by us for Android which processes the acquired data takes decision appropriately in real-time towards switching off the music.

  3. The interface is built by us towards making the system complete.

  4. Advancements in the cloud is also utilized to store the data

Technologies Used

  1. FITBIT
  2. Embedded Systems
  3. Data Analytics
  4. AI

Repository

http://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=ijmei

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