User:Samuel Herec/OSA

Obstructive Sleep Apnea (OSA) Obstructive Sleep Apnea (OSA) is a disease that causes the uppermost airways of an individual to be blocked during sleep. It occurs in approximately twenty percent of the world's population and more than half of 50-year-old men [1]. It is commonly characterized by a narrowing of the upper airway muscles. This airway muscles will flap and oscillate causing a vibration commonly referred to as snoring. The apneas in breathing during sleep affect the individual's quality of sleep and in turn quality of life [2]. If left untreated, OSA can cause daytime sleepiness, cardiovascular events such as hypertension, angina, arrhythmias, and cardiac arrest, myocardial infarction, memory loss, and sudden death [1], [2].

Detection The most comprehensive test, polysomnography (PSG), involves placing adhesive electrodes on a patient’s body and connecting them via wires to a data acquisition device to notate physiological signals during sleep [1], [2]. The wires attached to the sensors often obstruct the patients’ movement in their sleep and cause discomfort. To avoid the use of tethered sensors, a static-charge sensitive bed has been used to record the sleep stages of infants and young children. Data was collected of periodic leg movements to determine what stage of sleep the subject was in. Pressure sensors in an inflated mattress have been used to measure and monitor the sleep of other subjects. Pulse rate sensors can be put inside of pillows and mattresses as well [1].

Sensors Electromechanical film (EMFi) sensor strips are placed on a subject between their shoulder blades, near the jugular vein, on the sternum, and just above the ankle. The electromechanical material is a plastic film covered with several polarized, electrically conductive layers. Pressure on the strips causes a static charge to be generated. These static charges can be measured and depending on the location of the sensor strip the severity of a snoring episode can be determined [4]. Polyvinylidene Flouride (PVDF) sensors placed inside of an ergonomic pillow also detect snoring episodes. When an external pressure is exerted on the sensor, the piezoelectric qualities of the material induce an electrical signal on the electrodes of the sensor [6]. Typically two sensors are used in tandem. One sensor is to determine the ambient noise level of a room, and the other is to detect snoring [1]. Microphones Microphones can be implemented in snoring detection. A microphone can be placed approximately one to three feet from an individual. A filter circuit must be implemented to eliminate unwanted noise and can be adjusted with a potentiometer to adapt to different room conditions [5]. To eliminate ambient noise, an omni-directional microphone can be used instead [8]. It is placed on the suprasternal notch of a subject. The rate and flow of respiration dictates the strength of the signal from the microphone. Often a pulse oximeter is used in conjunction with the microphone to verify oxygen levels in blood. Oxygen levels typically drop at least four percent during an apnea event. The signal which indicates a snore occurs approximately ten seconds before this drop [9]. The microphone in a mobile phone can be used to detect apnea events. Replacing or attaching an additional microphone that is sensitive to low-pressure frequency waves enables the device to record sleep apnea data remotely. The microphone would have an expanded low-frequency response; from 20 Hz, typical of most microphones in cellular devices, to 0.1 Hz. The mobile device, placed in a thin air cushion underneath a bed mattress, can measure body movement, heartbeats, respiration, and snores through the mattress material. This is a portable detection method. A mobile phone would be able to transmit the data to a healthcare center so a subject’s condition could be monitored [10].

Accelerometers Accelerometers are proving to be equally as effective as PSG sensors and capacitive microphones at snoring detection. The accelerometer is placed on a subject near their trachea and can detect movements in this area up to 1kHz. An accelerometer is commonly used in conjunction with a microphone and PSG sensor setup. Studies have shown that the PSG sensor and microphone components of the snoring detection data can be extracted from accelerometer data, thus eliminating the need for microphones and PSG sensors when an accelerometer is being implemented [7].

Treatment

Electromechanical

A common solution is an ergonomic pillow, consisting of two humps, containing an air bladder, positioned behind the subject’s neck [3], [5]. The air bladder in one device provides seven different levels of inflation, checking the subject’s response after each level has been reached [1]. Full-body air bladders are another implementable solution. The patient is supported by the air bladder and two pressure sensors are used to record data from the patient. The two sensors are also small air bladders and simultaneously adjust their air pressure depending on the response of the patient [3].

A variation on an airbladder behind the neck of the subject is a sliding lever mechanism contained inside of a pillow. It is designed to move the sleeper’s head in the same fashion. The slider moves along three different tracks, moving from one end of the pillow to the other. The slider stops if the patient stops snoring. If the subject does not have their head on the angled slider surface while they are sleeping and the slider is moving, they experience a vibration sensation. This causes them to adjust their head during sleep and stops an occurring episode of snoring [5].

[1] R. Wei, X. Li, H. J. Kim, H. S. Kim, and J. J. Im, “A Development of Mechanism for Reducing Snoring,” ICEIE, Vol. 2, pp. 242- 245, 2010.

[2] N. Ben-Israel, A. Tarasiuk, and Y. Zigel, “Nocturnal Sound Analysis for the Diagnosis of Obstructive Sleep Apnea,” IEEE, Buenos Aires, Argentina, Sept. 4, 2010.

[3] J. H. Shin, Y. J. Chee, D.U. Jeong, and K. S. Park, “Nonconstrained Sleep Monitoring System And Algorithms Using Air-Mattress With Balancing Tube Method,” IEEE Transactions On Information Technology In Biomedicine, Vol. 14, No. 1, pp. 147- 156, January, 2010.

[4] J. Alametsa, J. Viik, E. Huupponen, A. Kulkas, A. Varri, and S. L. Himanen, “Snoring seconds detection with EMFi sensor strips,” BEC2010, Tallinn, Estonia, pp. 265- 268, October 6, 2010.

[5] R. Suryawanshi, S. D. Gunjal, and A. S. Pote, “Mobile Operated Anti-Snoring Pillow,” Second International Conference on Environmental and Computer Science, pp. 441- 444, 2010.

[6] S. Rajala, and J. Lekkala, “Film-type Sensor Materials PVDF and EMFi in Measurement of Cardiorespiratory Signals – A Review,” IEEE, pp. 1 – 8, 2010

[7] D. S. Morillo, J. L. R. Ojeda, L. F. C. Foix, and A. L. Jimenez, “An Accelerometer- Based Device for Sleep Apnea Screening,” IEEE Transactions On Information Technology In Biomedicine, Vol. 14, No. 2, pp. 491- 499, March, 2010.

[9] A. Yadollahi, E. Giannouli, and Z. Moussavi, “Sleep apnea monitoring and diagnosis based on pulse oximetery and tracheal sound signals ,” Medical and Biological Engineering and Computing, Vol. 48, No. 11, pp. 1087-1097, November, 2010.

[8] A. Yadollahi and Z. Moussav, “Automatic breath and snore sounds classification from tracheal and ambient sounds recordings,” Medical Engineering and Physics, Vol. 32, No. 9, pp. 985-990, November, 2010.

[10] K. Watanabe, Y. Kurihara, T. Nakamura, and H. Tanaka, “Design of a Low- Frequency Microphone for Mobile Phones and Its Application to Ubiquitous Medical and Healthcare Monitoring,” IEEE Sensors Journal, Vol. 10, No. 5, pp. 934-941, May, 2010.