A Report of Monitoring Sleep with Force Sensor Measurement-Joonas Paalasinaa

Many things such as measurements, signal processing methods, sensor, rate analysis, force, methods, sleep measurement, rate detection, and signal processing are explained in the report. Inside the report you can find things like heart rate, signal, sensors, analysis methods, rate measurement, respiratory, research, and force sensors.

The report presents discussion such as measurement methods, force sensor signal, information, film sensor, signal analysis methods, monitoring, implementation, force sensor measurement, and respiration rate variability. Below are excerpted from the report:

The heartbeat interval (ta , tb ) is accepted if the average Good tb candidate, small residual 60 40 20 (a) 0 −20 −40 −60 xa xb ta tb 60 40 20 (b) 0 −20 −40 −60 Observed signal Reconstructed signal 60 40 20 (c) 0 −20 −40 −60 0 .0 average( 2 i) Residual = 5 .8 region end region start 0 .5 1 .0 1 .5 2 .0 Time (seconds) 2 .5 3 .0 3 .5 Bad tb candidate, large residual 60 40 20 (a) 0 −20 −40 −60 xa xb ta tb 60 40 20 (b) 0 −20 −40 −60 Observed signal Reconstructed signal 60 40 20 (c) 0 −20 −40 −60 0 .0 average( 2 i) region end region start 0 .5 1 .0 Residual = 137.8 1 .5 2 .0 Time (seconds) 2 .5 3 .0 3 .5 Figure 3.7: Beat-to-beat interval evaluation in cases where the residual is low (a, b, c in the upper panel) and high (a, b, c in the lower panel). Based on those results, the following sleep analyses are calculated in the morning: • Sleep staging into the following phases: wakefulness, REM sleep, light sleep and d

Giving more content, the report contains more such as respiration, respiration signal, sleep monitoring, method, force sensor, measurement, processing methods, and sensor measurement.

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