WO2017134681A4 - Sleep monitoring and tracking system and method thereof - Google Patents
Sleep monitoring and tracking system and method thereof Download PDFInfo
- Publication number
- WO2017134681A4 WO2017134681A4 PCT/IN2017/050036 IN2017050036W WO2017134681A4 WO 2017134681 A4 WO2017134681 A4 WO 2017134681A4 IN 2017050036 W IN2017050036 W IN 2017050036W WO 2017134681 A4 WO2017134681 A4 WO 2017134681A4
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- occupant
- data
- sleep
- vibration data
- sensing device
- Prior art date
Links
- 230000007958 sleep Effects 0.000 title claims abstract 19
- 238000000034 method Methods 0.000 title claims abstract 9
- 238000012544 monitoring process Methods 0.000 title claims abstract 6
- 238000004891 communication Methods 0.000 claims abstract 6
- 230000008667 sleep stage Effects 0.000 claims abstract 6
- 206010028347 Muscle twitching Diseases 0.000 claims 6
- 230000037053 non-rapid eye movement Effects 0.000 claims 6
- 206010041235 Snoring Diseases 0.000 claims 3
- 238000010801 machine learning Methods 0.000 claims 2
- 230000004461 rapid eye movement Effects 0.000 claims 2
- 230000029058 respiratory gaseous exchange Effects 0.000 claims 2
- BQCIDUSAKPWEOX-UHFFFAOYSA-N 1,1-Difluoroethene Chemical compound FC(F)=C BQCIDUSAKPWEOX-UHFFFAOYSA-N 0.000 claims 1
- 238000013528 artificial neural network Methods 0.000 claims 1
- 206010062519 Poor quality sleep Diseases 0.000 abstract 1
- 230000036385 rapid eye movement (rem) sleep Effects 0.000 abstract 1
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Measuring devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
- A61B5/1113—Local tracking of patients, e.g. in a hospital or private home
- A61B5/1115—Monitoring leaving of a patient support, e.g. a bed or a wheelchair
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4812—Detecting sleep stages or cycles
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4815—Sleep quality
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Surgery (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- Engineering & Computer Science (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Physics & Mathematics (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Physiology (AREA)
- Dentistry (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
Abstract
A sleep monitoring and tracking system (100) is provided. The sleep monitoring and tracking system (100) comprising a sensing device (102) for measuring sleep related data of an occupant and a server (106) communicatively coupled to the sensing device (102) via a communication network. The sensing device (102) comprises a set of sensor units (110) configured to sense bedtime-related data of the occupant and a transmitter unit for transmitting occupancy and/or the bedtime-related data. The server (106) comprises a communication module (126) for receiving bedtime-related data of the occupant from the sensing device (102), a processor (124) for processing the bedtime-related data of the occupant to generate sleep related data for the occupant, a memory (122, 128) for storing sleep related data of the occupant and a User Interface (130) (UI) for providing display of sleep related data of the occupant. A method of analyzing sleep data and identifying sleep pattern and sleep stages namely light sleep, deep sleep and REM sleep of a user using the sleep monitoring and tracking system (100) is also described.
Claims
1. A sleep monitoring and tracking system (100) comprising:
a sensing device (102) that measures a plurality of vibration data of an occupant, wherein the plurality of vibration data of the occupant comprises (i) heart beat data, (ii) inhalation and exhalation data, (iii) body movement data, and (iv) muscle twitch data, wherein the sensing device (102) comprises:
a set of sensor units (110) that capture the plurality of vibration data of the occupant, wherein the set of sensor units (110) extract (i) heart rates from the heart beat data (ii) breathing rates from the inhalation and exhalation data, (iii) body movement signal from the body movement data and (iv) muscle twitch signal from the muscle twitch data to obtain a plurality of extracted vibration data of the occupant, wherein the set of sensor units (110) are placed below a mattress or above a bed; and
a transmitter unit (112) that transmits the plurality of extracted vibration data of the occupant;
a server (106) that receives the plurality of extracted vibration data of the occupant te from the sensing device (102) via a communication network, wherein the server (106) comprises:
a communication module (126) comprises a receiver module and a transmitter module,
15
wherein the receiver module receives the plurality of extracted vibration data from the transmitter unit (112) of the sensing device (102) via the communication network; a database (128) that stores the plurality of extracted vibration data from the set of sensor units (110); and
a processor (124) that processes the plurality of extracted vibration data of the occupant and determines a sleep stage of the occupant by employing a machine learning algorithm which receives the plurality of extracted vibration data of the occupant as input; and
an alarm that makes an alert to the occupant when the occupant completes a pre- determined number of sleep cycles, wherein each sleep cycle comprises a plurality of sleep stages.
2. The system of claim 1, wherein the plurality of vibration data of the occupant comprises snoring data, wherein the set of sensor units (110) extract the snoring signals from the snoring data, wherein the set of sensor units (110) capture room temperature data, humidity data, light data, air quality data and noise level data around the occupant.
3. The system of claim 1 , wherein the plurality of sleep stages comprises (i) Non-Rapid Eye Movement (NREM), (ii) Rapid Eye Movement (REM), wherein the NREM comprises (i) NREM 1 , (ii) NREM 2 and (iii) NREM 3.
16
4. The system of claim 1, wherein the sensing device (102) comprises multiple sets of sensor units (110) for capturing the plurality of vibration data for each occupant.
5. The system of claim 4, wherein each set of sensor units (110) comprises an array of Piezoelectric Vinylidene Fluoride (PV DF) sensors.
6. The system of claim 1, wherein the the server (106) (i) detects a plurality of sleep irregularities of the occupant, and sends a notification to a designated recipient, wherein the notification comprises a suggestion for the sleep irregularities, wherein the suggestion chosen from the database (128) that lists the sleep irregularities mapped against the suggestion.
7. The system of claim 1, wherein the server (106) classification hypothesis and neural network (125) is trained on the extracted features using chronological plurality of vibration data from polysomnography.
8. The system of claim 1, wherein the set of sensor units (110) check if the occupant is on the mattress.
9. A method for sleep monitoring and tracking, the method comprising:
17
measuring a plurality of vibration data of an occupant, wherein the plurality of vibration data of the occupant comprises (i) heart beat data, (ii) inhalation and exhalation data, (iii) body movement data and (iv) muscle twitch data;
capturing the plurality of vibration data of the occupant;
extracting (i) heart rates from the heart beat data (ii) breathing rates from the inhalation and exhalation data, (iii) body movement signal from the body movement data and (iv) muscle twitch signal from the muscle twitch data to obtain a plurality of extracted vibration data of the occupant;
transmitting the plurality of extracted vibration data of the occupant from a sensing device (102) to a server (106) via a communication network;
receiving the plurality of extracted vibration data of the occupant to from the sensing device (102) by the server (106);
dividing the plurality of extracted vibration data of the occupant corresponding to the occupant into a plurality of sub intervals;
determining a sleep stage of the occupant by employing a machine learning algorithm which receives the plurality of extracted vibration data of the occupant as input;
alerting the occupant when the occupant completes a pre -determined number of cycles, wherein each sleep cycle comprises a plurality of sleep stages.
10. The method of claim 9, wherein the method comprises the step of checking if the occupant is on the mattress.
18
11. The method of claim 9, wherein the method comprises the step of measuring the plurality of sensor units (110) in a sensing device (102) that are active.
19
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| IN201641003985 | 2016-02-04 | ||
| IN201641003985 | 2016-02-04 |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| WO2017134681A2 WO2017134681A2 (en) | 2017-08-10 |
| WO2017134681A3 WO2017134681A3 (en) | 2017-11-23 |
| WO2017134681A4 true WO2017134681A4 (en) | 2018-03-29 |
Family
ID=59499557
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/IN2017/050036 WO2017134681A2 (en) | 2016-02-04 | 2017-01-24 | Sleep monitoring and tracking system and method thereof |
Country Status (1)
| Country | Link |
|---|---|
| WO (1) | WO2017134681A2 (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11648373B2 (en) | 2013-07-08 | 2023-05-16 | Resmed Sensor Technologies Limited | Methods and systems for sleep management |
| CN105592777B (en) | 2013-07-08 | 2020-04-28 | 瑞思迈传感器技术有限公司 | Method and system for sleep management |
| LU100993B1 (en) | 2018-11-09 | 2020-05-11 | Visseiro Gmbh | SENSOR SURFACE |
| JP7301275B2 (en) * | 2021-06-25 | 2023-07-03 | ヘルスセンシング株式会社 | Sleep state estimation system |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070276439A1 (en) * | 2004-03-16 | 2007-11-29 | Medtronic, Inc. | Collecting sleep quality information via a medical device |
| US7942824B1 (en) * | 2005-11-04 | 2011-05-17 | Cleveland Medical Devices Inc. | Integrated sleep diagnostic and therapeutic system and method |
| US20130030257A1 (en) * | 2010-05-14 | 2013-01-31 | Kai Medical, Inc. | Systems and methods for non-contact multiparameter vital signs monitoring, apnea therapy, apnea diagnosis, and snore therapy |
-
2017
- 2017-01-24 WO PCT/IN2017/050036 patent/WO2017134681A2/en active Application Filing
Also Published As
| Publication number | Publication date |
|---|---|
| WO2017134681A3 (en) | 2017-11-23 |
| WO2017134681A2 (en) | 2017-08-10 |
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