Apnea, a cessation in breathing is critical condition that affects the person regardless of age.

In infants, an apneic state occurs when there is an absence of respirations for 20 seconds (Alvaro & Rigatto, 2012). In adults, there is a correlation between sleep apnea with increased risks of cardiovascular health problems (Wimms, Woehrle, Ketheeswaran, Ramanan, & Armitstead, 2016; Wu, Yuan, Wang, Sun, Liu, and Wei, 2016; Hao, Xiandao, Li, Jingwu, Jinghua, & Yongxiang, 2016).

The purpose of this proposed study is to investigate the reliability of a smart bed sheet's ability to detect physiological signals such as respiratory patterns.

The study's goals are two-fold: 1) to determine the sensors' ability to detect patterns with regards to input signals, and 2) to evaluate the efficacy of pressure sensor signals collected in relaying respiratory rate and respiratory patterns to monitor different thresholds of respiration rate and pattern which may include critical parameters dangerously outside of life sustaining norms.

Sudden Infant Death Syndrome is one of the leading causes of death in infants (Hospital for Sick Children, 2016; Children's Hospital of Philadelphia, 2016). The first few years are crucial as many factors contribute to infants' healthy development and much of the critical growth period occurs during sleep. Newborns spend the majority of a day sleeping, up to 16 hours (Parmelee, Shulz, & Disbrow, 1961). Infants generally breathe irregularly with significant breath-to-breath variability and periodic breathing characterizing regular and apneic states (Alvaro & Rigatto, 2012). However, when an abnormal rhythm or apneic period arises, the situation becomes critical with a limited window of opportunity to save the life of a newborn (e.g., Sudden Infant Death Syndrome or Bradycardia). An apneic state occurs when there is an absence of respirations for 20 seconds (Alvaro & Rigatto, 2012). The characterization of apnea can be divided into different states such as obstructive apnea, central apnea, and mixed apnea. Emerging literature in adults indicate a correlation between sleep apnea with increased risks of cardiovascular health problems (Wimms, Woehrle, Ketheeswaran, Ramanan, & Armitstead, 2016; Wu, Yuan, Wang, Sun, Liu, and Wei, 2016; Hao, Xiandao, Li, Jingwu, Jinghua, & Yongxiang, 2016). With the ultimate goal of early detection of changes in respiratory rates and patterns, improved methods of monitoring and detection along with sounding an alarm will allow for early intervention and potential prevention of death or critical illness.

The study involves evaluating the sensor effectiveness on healthy human participants. The participants will spend one night sleeping on the functional bed sheet in the Nursing Simulation Centre at York University. Pressure signals will will be recorded during the night, and later evaluated for the respiration rate and patterns. Hourly during sleep, the researcher will assess and document participants' respiratory rates and patterns, and pulse oximeter readings (which includes the oxygen saturation reading and heart rate). Audio-visual recording of the participants during their sleep will be captured for support of the interpretation of signal anomalies. The data collected from the functional bed sheet will be compared to clinical grade hourly manual monitoring of the respiratory rates and patterns by reseachers and registered nurses.

Paricipants will complete a pre-screening form prior to settling in for the night. When ready for sleep, participants will be directed to position themselves on the bed sheet and through a variety of different sleeping positions (back, front, right side, left side) to establish a baseline. During sleep, the sensors on the functional bed sheet will capture participants' movement and respiratory indicators. Hourly, the researcher will obtain the physiological findings of respiratory rate and rhythm (obtained through observation), and heart rate and oxygen saturation level (obtained from the pulse oximeter)

This study will be followed by a pre-clinical study conducted with infant and adult high technology mannequins. The pre-clinical study evaluates the efficacy of the functional bed sheet sensors to detect pressure variations, respiratory rates and patterns both within normal and abnormal limits. Researchers will evaluate sensor data looking for signal deviances. This phase is fundamental and will provide evidence to support the clinical study that evaluates the effectiveness of the device on human participants.

Inclusion Criteria:

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Exclusion Criteria:

• no known sleep-related disorders
• use of sleep medication