System and process for non-invasive collection and analysis of physiological signals
A system and method for detecting, monitoring and analyzing physiological characteristics. Signals from a subject are acquired from a suite of sensors, such as temperature, carbon dioxide, humidity, light, movement, electromagnetic and vibration sensors, in a passive, non-invasive manner. The signals are processed, and physiological characteristics are isolated for analysis. The system and method are to analyze sleep patterns, as well as to prevent bed sores or detect conditions such as illness, restless leg syndrome, periodic leg movement, sleep walking, or sleep apnea. However, numerous other applications of the invention are also disclosed.
1. A non-invasive system for assessing physiological characteristics of a subject, said system comprising:
a network of sensors configured to provide electronic output signals indicative of at least one sensed condition, said network including at least one passive sensor selected from the group consisting of vibration, temperature, carbon dioxide, humidity, electromagnetic and light sensors;
data acquisition circuitry for collecting the electronic signals output from said network of sensors;
a processor configured to process the electronic signals, said processor including an amplifier configured to amplify at least one of the electronic signals, and first and second filters configured to receive the amplified electronic signals to produce two processed electronic signals, wherein said first filter includes a band pass filter and said second filter includes a low pass filter and a high pass filter; and
an output device for outputting the processed signals into human-readable data indicative of at least one condition of a subject, wherein said human-readable data comprises a subject movement percentage.
2. The system of claim 1 wherein said system is adapted to assess the quality of sleep of a subject and wherein: said data acquisition circuitry is configured to collect the electronic signals output from said network of sensors indicative of at least one of heart rate and respiratory rate;
said first filter receives signals indicative of chest movement and said second filter receives signals indicative of heart movement; and
said processor includes an algorithm to generate at least one of a heart rate and a respiratory rate based on processed electronic signals output at or below about 50 Hz.
3. The system of claim 2 , wherein:
said band pass filter comprises a second order band pass filter, an active filter and a filter with both cutoff frequencies below about 1 Hz;
said low pass filter comprises a second order low pass filter, an active filter and a filter with a cutoff frequency below about 1 Hz; and
said high pass filter is a third order high pass filter, an active filter and has a cutoff frequency below about 50 Hz.
4. The system of claim 1 , further comprising a microcontroller for converting the collected electronic signals into a bit stream to be logged into a data file for immediate analysis or for later review.
5. The system of claim 1 , wherein said network of sensors includes at least one detector for sensing motion, the bit stream includes electronic signals from said at least one detector and said processor processes the bit stream to provide a positional map of the subject.
6. The system of claim 5 , wherein said at least one detector comprises a matrix of pressure-sensitive contact switches that are embedded in a mattress pad, block of foam, bed sheet, or a chair, said matrix providing electronic signals corresponding to a positional map of the subject.
7. The system of claim 1 , wherein said amplifier comprises an instrumentation amplifier that provides buffering from said network of sensors and an infinite common mode rejection ratio.
8. The system of claim 1 , wherein said first filter outputs a first signal corresponding to a respiratory rate on a breath-by-breath basis of the subject and said second filter outputs a second signal corresponding to a heart rate on a beat-by-beat basis of the subject.
9. The system of claim 1 , wherein at least some of the sensors are passive sensors requiring no active involvement from the subject and no direct attachment to the subject.
10. The system of claim 9 , wherein all of the sensors are passive sensors requiring no active involvement from the subject and no direct attachment to the subject.
11. The system of claim 1 , wherein human-readable data comprises at least one of a heart rate waveform and a respiratory waveform.
12. The system of claim 1 , wherein the human-readable data comprises an obstructive sleep apnea count.
13. The system of claim 1 , wherein said network of sensors further comprises a movable support including at least one of said sensors.
14. The system of claim 1 , wherein said human-readable data comprises data describing electromagnetic information collected by said sensor configured to sense electromagnetic signals.
15. The system of claim 1 , wherein at least part of the system is incorporated in one of a mattress pad or pillow, a bed or chair at a sleep lab, a bed or chair at an elder care facility, a bed or chair at a hospital for children or adults, a bed or baby support at a prenatal care facility, and a publicly available health monitoring station.
16. A non-invasive system for assessing physiological characteristics of a subject, said system comprising:
means for passively detecting physiological characteristics and providing electronic output signals indicative of at least one sensed condition, the physiological characteristics including at least one characteristic selected from the group consisting of vibration, temperature, relative humidity, carbon dioxide, electromagnetic and light;
means for collecting the electronic signals output from said passive detection means;
means for processing the electronic signals, including: means for amplifying at least one of the electronic signals;
first means for filtering the amplified electronic signal to generate a first processed signal;
second means for filtering the amplified signal to generate a second processed signal; and
means for outputting the processed signals into human-readable data indicative of at least one condition of a subject, wherein said human-readable data comprises a subject movement percentage.
17. The system of claim 16 , wherein the first processed signal corresponds to a respiratory rate on a breath-by-breath basis of the subject and the second processed signal corresponds to the heart rate on a beat-by-beat basis of the subject.
18. A method of analyzing physiological characteristics of a subject including cardiac and/or respiratory parameters on a beat-by-beat or breath-by-breath basis, said method comprising the steps of:
passively detecting physiological characteristics through a network of sensors requiring no conscious input by the subject and being capable of providing electronic output signals indicative of a sensed condition, the network including at least one sensor selected from the group consisting of vibration, position, temperature, relative humidity, carbon dioxide, electromagnetic and light sensors;
collecting the electronic signals output from the network of sensors;
processing the electronic signals such that at least one of the electronic signals is amplified and fed to first and second filters to produce two processed electronic signals, wherein the first filter includes a band pass filter and the second filter includes a low pass filter and a high pass filter, and wherein the processed signals correspond to a subject movement percentage; and
outputting the processed signals into human-readable format.
19. The method of claim 18 , further comprising processing the processed electronic signals to generate a heart rate and a respiratory rate.
20. The method of claim 18 , further comprising converting the collected electronic signals into a bit stream to be logged into a data file for immediate analysis or for later review.
21. The method of claim 20 , further comprising processing the bit stream to provide a positional map of the subject relative to the network of sensors.
22. The method of claim 18 , wherein the step of amplifying the at least one electronic signal comprises amplifying using an instrumentation amplifier that provides buffering from the network of sensors and an infinite common mode rejection ratio.
23. The method of claim 18 , wherein said processing step further comprises the first filter outputting a first signal corresponding to a respiratory rate on a breath-by-breath basis of the subject and the second filter outputting a second signal corresponding to the heart rate on a beat-by-beat basis of the subject.
24. The method of claim 18 , wherein the processed signals correspond to at least one of a heart rate waveform and a respiratory waveform.
25. The method of claim 18 , wherein the processed signals correspond to an obstructive sleep apnea count.