AU2020104028A4 - IAS- Patients Monitoring System: Monitoring of High-Risk Indian Patients Using Artificial Intelligence System - Google Patents

Abstract

Our Invention" IAS- Patients Monitoring System" is a method and system for remote monitoring of high-risk patients using artificial intelligence and a plurality of high-risk patients can be simultaneously monitored without patient intervention. The invention is a patient hears questions in the doctor's voice at each monitoring encounter and responds and the patient's responses are recorded at a remote central monitoring station and can be analyzed on line or later. The IAS- patients monitoring system is an artificial intelligence-Al and voice technology are combined to present to the patient during a monitoring session or encounter questions which would be selected from a plurality of different recorded questions. The invented system also includes the questions to the patient are chosen using Al, based on the patient's response by parsing and the monitor could take several forms such as for e.g., uterine activity strips, glucometers, blood pressure cuffs, pulse monitors, electroencephalographs, etc. Preferably, four telephone lines are dedicated to each patient. The invented system also includes one for the monitor, one for the voice, one as a backup and one to sense failures and dual tone matrix frequency signals may be used for transmission of monitored signals and other information which can be recognized by system which is but one example of the voice technology which can be used. 21 'KNOWN" HMO PATIENTS HEATH CARE 103 PRACTITIONER -102 VvTH -l "" 1N00UN110* TELEPHONE WITH OPTIOl@AL &MODRS BOTH MONIfERING DEVICE VOICE AND DATA WITHOUT PATIENT IG INTERVENTION DATA ACQUISITION FO0R MONITORING V01CE RECOGNITION DIGITIZED V04CE NATURAL LANGUAGE BUILT WITH OBJECT ORIENTED PROGRAMMING EXPERT SYSTEMS CAPTURE OF *ENOOUNE~f DATA DATA DATA DATA PIPELINE: DATA CLEANING SOURCE TYPES CUR ATION & MODELING FIG.~~~~~~~............... 1:ILUSRAE.APITOIA. EPESNTTONOFA.EMT.MNIORN.SSTM.SIG(A).XPR SYSTEMS~~~~~~~~~~~..... WHRINECHNW. OITRN.CNAC.NIITE.Y.H.EATCAEPRCITOE WITH.................... A.KNOWN.HMOPATIENT.ISTERMED.AN.ENCOUNTER"

Description

'KNOWN" HMO PATIENTS

HEATH CARE 103 PRACTITIONER -102 VvTH ""-l 1N00UN110* TELEPHONE WITH OPTIOl@AL &MODRSBOTH MONIfERING DEVICE VOICE AND DATA WITHOUT PATIENT IG INTERVENTION

DATA ACQUISITION FO0R MONITORING V01CE RECOGNITION DIGITIZED V04CE NATURAL LANGUAGE BUILT WITH OBJECT ORIENTED PROGRAMMING EXPERTSYSTEMS CAPTURE OF *ENOOUNE~f DATA DATA DATA DATA PIPELINE: DATA CLEANING SOURCE TYPES CUR ATION & MODELING

FIG.~~~~~~~............... 1:ILUSRAE.APITOIA. EPESNTTONOFA.EMT.MNIORN.SSTM.SIG(A).XPR SYSTEMS~~~~~~~~~~~..... WHRINECHNW. OITRN.CNAC.NIITE.Y.H.EATCAEPRCITOE WITH....................A.KNOWN.HMOPATIENT.ISTERMED.AN.ENCOUNTER"

IAS- Patients Monitoring System: Monitoring of High-Risk Indian Patients Using Artificial Intelligence System

FIELD OF THE INVENTION

Our invention "AS- Patients Monitoring System" is related to monitoring of high-risk Indian patients using artificial intelligence system and also relates generally to simultaneous remote monitoring of a plurality of high risk patients by a healthcare practitioner and also concerns simultaneous remote monitoring of a plurality of high risk patients without patient intervention and using artificial intelligence (AI).

BACKGROUND OF THE INVENTION

Continual patient monitoring in certain types of patient condition becomes a necessity to assure timely intervention by a healthcare practitioner or a physician to initiate the right medical procedure or administer the required medication in a timely manner. Situations with high-risk patients in the areas of cardiology, obstetrics, neurology, psychology are but some examples where continual remote patient monitoring becomes a patient care necessity.

With increasing hospitalization costs for patients, health insurance companies and health maintenance organizations are encouraging more and more patients to reduce the duration of hospitalization if hospitalization is an absolute necessity. In the face of increasing healthcare costs, certain kinds of treatment, including chemotherapy, antibiotic therapy, infusion therapy and pneumonia treatment are all considered relatively safe, cost effective home treatments. Several infusion devices have been approved by the FDA with the proviso that such devices be calibrated at regular intervals as prescribed.

There are other situations such as in the field of obstetrics wherein patients are encouraged to wait as long as medically desirable before patients enter a hospital for childbirth. Typically, in the obstetrics patient situation, a patient, by home monitoring of the frequency and duration of uterine contractions can determine if it is time to enter a hospital or any other facility for childbirth. Such determination however needs patient participation or intervention. There may be situations however, where patient participation is not possible or patient intervention is not to be relied upon, but patient monitoring is nevertheless necessary. Another example of such a situation is a cardiac patient.

A reliable but expensive method of monitoring in such situations is for a nurse or healthcare worker or a physician to meet the patient in person to do the monitoring. Notwithstanding, if continual monitoring is necessary, it will then necessitate the nurse or healthcare worker or physician to be physically present at the patient site during the monitoring. This will limit the number and type of patients that can be covered in a given time by a healthcare worker.

Some solutions to the above problem are offered by patient care monitoring services which sometimes are offered by health maintenance organizations (HMO). Statistics indicate that corporate healthcare benefits represented about 5% of the payroll in 1980 as compared with 14% in 1990. Part of the corporate healthcare benefits are patient monitoring costs, and reducing such costs will be a very attractive proposition. In any event it is important to note that avoidance of clinically unnecessary outpatient visits can be a key to reducing healthcare costs, if insurance liability can be reduced and the clinical integrity preserved.

It is known in prior art to generate signals representing a patient's condition and record them for later scrutiny by a physician. An example of such is the well known Holter heart monitor, wherein a continuous 24-hour cardiogram of a patient is recorded by a monitor which is worn by the patient. Functionally however, in such a monitoring system a healthcare worker or a physician is not alerted by any emergency situation which could occur during the duration of the monitoring. The underlying considerations in providing improved health monitoring services for high risk patients include the facts that:

(i) a high risk patient likes to hear the doctor's voice during the monitoring interaction;

(ii) the doctor has the responsibility to determine in a timely manner as to whether an appointment is necessary,

(iii) the doctor should have the opportunity of determining if the high risk patient is in need of any urgent medication or any change in the treatment,

(iv) it is often undesirable for monitoring to be done by patient intervention especially in situations like acute hypertension cases or serious perinatal cases.

(v) it is desirable to minimize the continuous use of a nurse or other healthcare worker to personally attend to the patient and do the monitoring,

(vi) it would be undesirable and disadvantageous to use acoustic telephone devices like modems which would be ineffective and uneconomical to use for remote monitoring purposes, and

(vii) it is desirable if a physician/doctor could attend simultaneously and remotely to a large number of high risk patients so that doctor intervention or other remedial measure could be initiated when necessary and no sooner.

Previous approaches by others to address this problem in general, as aforesaid, have been to use an intermediary, (a visiting nurse, or similar representative) to call on the patient, and take the physical data (temperature, pulse, blood pressure, fetal heart monitor, glucose level, etc., and report those results to the clinicians' office by mail or telephone. This means that only the recorded physical data is being obtained. The physical data must still be viewed by the doctor to evaluate his patient. And, again, another level of human intervention to monitor the patient is required for each patient. Health software services, such as Health dyne,@ Inc. use a nurse to transmit the data from the patient, and then their software evaluates the patient's medical condition. Both of these methods are costly because of the human intervention of a healthcare worker or a nurse visiting each patient.

This is not the same as a doctor himself, speaking to each of his high-risk patients, evaluating their need for attention, and obtaining the data from the monitoring devices on those patients simultaneously.

There is need for an improved patient monitoring system including method and apparatus, which is both patient friendly and doctor friendly and increases the patient care quality without increasing clinically unnecessary patient visits. There is also need for such a system to be accurate and reliable, to use normal telephone lines, to be easy for maintenance, future upgrading, additions and changes.

The present invention provides a health monitoring system including method and apparatus for monitoring, without patient intervention and using artificial intelligence, the medical condition of a remotely located patient by means of monitor-generated signals through telephone lines reaching an interface to the medical expert system application. Voice technology and Al are integrated in the innovative system offering significant economic benefits in the home healthcare industry. As described hereinafter, the Al used in the innovative health monitoring system is governed by physician-provided guidelines, standards and approach. Advantageously, the patient is presented questions in the physician's own voice, and the questions and their pattern would be chosen from prerecorded conversation of the physician which would be parsed and presented to the patient depending on the patient's response to each question and as guided by Al.

A clear benefit is perceived by the patients using the inventive monitoring system in that they view the physician "conversation" as providing an increased level of physician contact, concern and care. Such a patient perception becomes a significant marketing tool for the inventive system in the healthcare industry. The innovative monitoring system described hereinafter provides for simultaneous multiple monitoring of several high risk patients who might have different types of ailments. The system described and claimed herein allows a medical practitioner, hospital, or group health provider to expand their service market, without risk of losing quality of service.

In fact, it is the consistent application of the physician-provided rules of monitoring patient parameters that allows the system to advise the doctor routinely about his patients. He can be more productive because he is directed to critical patient needs, while unnecessary outpatient visits are reduced. Moreover, the fact that the multiple physician-patient "conversations" are initiated by the system, and can be carried on simultaneously, means that the physician is increasing his services without increasing his time to converse with patients.

Because of the A/Voice technology combination, appropriate clinical questions are asked, (through "reasoning" about a response, and branching to another relevant question, or portion of a question) --by a physician, forward and backward chaining in Artificial Intelligence. In addition, the A/Voice technology allows it to simultaneously carry on multiple (approximately 48) conversations, monitoring the results, and to include features such as call monitoring, call forwarding, and call recording whenever physician-directed rules indicate that intervention and alarming are needed.

Thus, if an HMO were providing high-risk pregnancy patients with home health monitoring, the obstetrician would be notified immediately of an out-of-limits fetal heart rate on a patient. The system would detect the change, notify the HMO monitoring assistant by opening a window on their computer screen, merging recent medical data on the patient, and also forwarding the call to the HMO monitoring assistant. It is to be noted that in all of its functionality, the Al/Voice/Monitoring is not intended to diagnose; rather it advises the clinician of possible need to intervene.

Physicians who would use the inventive monitoring system would easily view the system as a superior clinical tool, since it frees them from being tied to one high risk patient at a time and also since they are not relying upon a patient to read a monitoring device. The system allows a physician user to be warned of critically-ill patients automatically according to the physician's own chosen guidelines as controlled by the Al.

In a preferred embodiment described hereinafter a DECvoice 1-168 VAX System is used which offers the capability of simultaneously monitoring 48 remote patients all connected in to a central monitoring and recording system, such as for e.g., a computer integrated telephone system.

The practice of medicine is increasingly characterized by overwhelming amounts of information, new knowledge in diagnostics and therapeutics, and highly fragmented care environments, with potentially hundreds of different individuals delivering care to a single patient across healthcare settings. Coordinating clinical decisions to advance the care and treatment of patients within this environment poses significant challenges. Hospital readmission is an important example of the type of problems health systems face in allocating critical resources in the midst of this fragmented environment.

Many patients are unnecessarily readmitted to the hospital. A 2009 study published in the New England Journal of Medicine (Jencks, S. F., et al., "Prehospitalization among Patients in the Medicare Fee-for-Service Program," The New EnglandJournalof Medicine, 360 (2009): 1418-28) demonstrated that almost one-fifth of Medicare patients were readmitted to the hospital within 30 days of discharge and 34% were readmitted within 90 days. This research estimated that only 10% of these readmissions were planned and that the annual cost to Medicare alone of unplanned hospital readmissions exceeds $17 billion.

For example, patients with heart failure, the leading diagnosis for acute care hospitalization and readmissions for patients over the age of 65, face particular challenges in transitioning from the hospital to home, and hospital readmissions are common for these patients. Preparation for discharge is often fragmented, and many patients and families feel ill-prepared for discharge. Upon discharge, responsibility for management of patients reverts back to their primary care provider, who may have no record of the care or medications given during the hospital stay. This lack of coordinated care results in frequent readmissions, with a large percentage of patients discharged with heart failure being readmitted to the hospital within several months.

While not all readmissions are preventable, it is estimated that a significant percentage of heart failure readmissions is avoidable with better patient education, better communication with the patient and the patient's primary care provider, ensuring that the patient has appropriate follow-up scheduled at the time of discharge, and other targeted intervention and treatment. However, most hospitals fail to consistently implement most or all of these elements. Many interventions can be expensive and complicated to perform in the real world. One of the reasons why efforts can fail is that hospitals have difficulty identifying patients that are truly at risk for readmission and for which interventions should be a high priority.

If high-risk patients could be more easily and accurately identified early in their hospital stay (e.g., in the Emergency Room or upon admission), the right interventions could be performed on the population for which it is most needed, thereby lowering overall heart failure readmission rates. Today, most hospitals attempting to identify patients at risk are doing so manually, without leveraging the information available in their electronic health records. Hospital readmission is one of potentially thousands of adverse clinical events that could be prevented by electronic identification, targeting, coordinating and monitoring throughout the inpatient and outpatient environment. This disclosure describes software developed to identify and risk stratify patients at highest risk for hospital readmissions and other adverse clinical events.

Healthcare costs around the world have been rising. One reason is that, obesity is common, serious and costly. A Duke University study suggests that by 2030, about 42% of Americans will be obese, which is up from 36% in 2012 and will cost about $550 billion dollars. Even small reductions in obesity prevalence "could result in substantial savings," wrote the authors. Obesity-related conditions increase the odds of heart disease, stroke, type 2 diabetes and certain types of cancer, some of the leading causes of preventable death. In 2008, medical costs associated with obesity were estimated at $147 billion; the medical costs for people who are obese were $1,429 higher than those of normal weight.

Obesity affects some groups more than others. Non-Hispanic blacks have the highest age-adjusted rates of obesity (49.5%) compared with Mexican Americans (40.4%), all Hispanics (39.1%) and non-Hispanic whites (34.3%). Among non

Hispanic black and Mexican-American men, those with higher incomes are more likely to be obese than those with low income. Higher income women are less likely to be obese than low-income women. There is no significant relationship between obesity and education among men. Among women, however, there is a trend-those with college degrees are less likely to be obese compared with less educated women. Thus, education appears to be key. Between 1988-1994 and 2007-2008 the prevalence of obesity increased in adults at all income and education levels.

A government solution has been suggested. For example, a ban on the use of trans fats in NY restaurants has sharply reduced the consumption of these unhealthy fats among fast-food customers. However, the government and regulation may not be the best way to solve the problem.

To treat obesity in a cost effective manner, coordination is needed among different service providers such as dieticians, doctors, and exercise coaches. However, planning information, alerts and reminders may be haphazardly and intermittently distributed to doctors, clinicians, or their staff with existing healthcare appointment and scheduling systems and do not support multi-vendor calendaring system that shares information among the different providers. This occurs in other treatments as well.

For example, in the case of a patient scheduled for radiation therapy, an existing system may be aware of a necessary number of appointments and treatment orders, but these numbers typically are not compatible with the (e.g., one or more) treatment plans involved. Consequently, a clinician needs to work out a referral connection manually for each appointment. The existing systems also require manual coordination of appointments with treatment plan goals and treatment plan results which occupies a significant amount of clinician time in gathering, collating and analyzing information.

One way to monitor the impact of obesity is to monitor blood pressure. As discussed in U.S. Pat. No. 6,514,211, three well known techniques have been used to non-invasively monitor a subject's arterial blood pressure waveform: auscultation, oscillometric, and tonometry. The auscultation and oscillometric techniques use a standard inflatable arm cuff that occludes the subject's brachial artery. The auscultatory technique determines the subject's systolic and diastolic pressures by monitoring certain Krokoff sounds that occur as the cuff is slowly deflated.

The oscillometric technique, on the other hand, determines these pressures, as well as the subject's mean pressure, by measuring actual pressure changes that occur in the cuff as the cuff is deflated. Both techniques determine pressure values only intermittently, because of the need to alternately inflate and deflate the cuff, and they cannot replicate the subject's actual blood pressure waveform. Occlusive cuff instruments of the kind described briefly above generally have been effective in sensing long-term trends in a subject's blood pressure, but they have been ineffective in sensing short-term blood pressure variations.

The '211 patent discloses blood pressure measurement by determining the mean arterial blood pressure (MAP) of a subject during tonometry conditions. The apparatus has one or more pressure and ultrasound transducers placed over the radial artery of a human subject's wrist, the latter transmitting and receiving acoustic energy so as to permit the measurement of blood velocity during periods of variable compression of the artery.

During compression, the ultrasound velocity waveforms are recorded and processed using time-frequency analysis. The time at which the mean time frequency distribution is maximal corresponds to the time at which the transmural pressure equals zero, and the mean pressure read by the transducer equals the mean pressure within the artery. In another aspect of the invention, the ultrasound transducer is used to position the transducer over the artery such that the accuracy of the measurement is maximized.

PRIOR ART SEARCH

US4254304A *1977-09-261981-03-03E-Systems, Inc. Signal processor for use with a telephone system and a digital transmission line. US4426555A *1982-01-181984-01-17General Electric Company Telephone communications device for hearing-impaired person. US4803625A*1986-06-301989-02-07Buddy Systems, Inc. Personal health monitor. US4894787A*1988-04-281990-01-16Kaman Aerospace Corporation Automatic load monitoring system with remote sensing. US4962473A*1988-12-091990-10-091tt Corporation Emergency action systems including console and security monitoring apparatus. US5056513A*1989-05-291991-10-15Revo' Air Micro-air-wave detection device particularly for breathing monitoring and surveillance. US20030101076A12001-10-022003-05-29Zaleski John R. System for supporting clinical decision making through the modeling of acquired patient medical information. US20040122706A12002-12-182004-06-24Walker Matthew J. Patient data acquisition system and method. US20040122708A1*2002-12-182004-06-24Avinash Gopal B. Medical data analysis method and apparatus incorporating in vitro test data. US20040242972A12003-05-282004-12-02General Electric Company Method, system and computer product for prognosis of a medical disorder. US20050191716A12000-01-112005-09-OlZycare, Inc. Apparatus and methods for monitoring and modifying anticoagulation therapy of remotely located patients. US20050197982A1*2004-02-272005-09-080livier Saidi Methods and systems for predicting occurrence of an event.

OBJECTIVES OF THE INVENTION

1) The objective of the invention is to a method and system for remote monitoring of high-risk patients using artificial intelligence and a plurality of high-risk patients can be simultaneously monitored without patient intervention. 2) The other objective of the invention is to a patient hears questions in the doctor's voice at each monitoring encounter and responds and the patient's responses are recorded at a remote central monitoring station and can be analyzed on line or later. 3) The other objective of the invention is to an artificial intelligence-Al and voice technology are combined to present to the patient during a monitoring session or encounter questions which would be selected from a plurality of different recorded questions. 4) The other objective of the invention is to the questions to the patient are chosen using Al, based on the patient's response by parsing and the monitor could take several forms such as for e.g., uterine activity strips, glucometers, blood pressure cuffs, pulse monitors, electroencephalographs, etc. 5. The other objective of the invention is to the monitor, one for the voice, one as a backup and one to sense failures and dual tone matrix frequency.

SUMMARY OF THE INVENTION

A monitoring system for a person includes a processor coupled to one or more wireless nodes; a wearable mobile appliance in communication with the client and one or more wireless nodes; and one or more computer implemented agents with rules executed by the processor, the rules being selected to respond to a client communication relating to a predetermined health condition, each agent communicating with another computer implemented agent, the client or the treatment professional, and upon receiving a communication from the client, the processor selecting one or more computer implemented agents to reply with an instruction on healthy client behavior.

Advantages of the preferred embodiment may include one or more of the following. The system turns obesity and overweight into preventable phenomena, and the myriad health problems associated with them. The system not saves money and enhances lives by continued efforts at getting the weight off. The system brings awareness of the serious health issues-physical and mental-that are linked to being overweight or obese, along with the tried and true lifestyle changes like diet and exercise, as ways for battling the obesity epidemic.

In another aspect, a heart monitoring system for a person includes one or more wireless nodes; and a wearable appliance in communication with the one or more wireless nodes, the appliance continuously monitoring patient vital signs or other data such as cardiac abnormalities. Embodiments can monitor heart rate, heart rate variability, respiratory rate, fluid status, posture and activity.

In a further aspect, a monitoring system for a person includes one or more wireless nodes; and a wristwatch having a wireless transceiver adapted to communicate with the one or more wireless nodes; and an accelerometer to detect a dangerous condition and to generate a warning when the dangerous condition is detected.

In yet another aspect, a heart monitoring system for a person includes one or more wireless nodes forming a wireless network and a wearable appliance having a sound transducer coupled to the wireless transceiver; and a heart disease recognizer coupled to the sound transducer to determine cardiovascular health and to transmit heart sound over the wireless network to a remote listener if the recognizer identifies a cardiovascular problem. The heart sound being transmitted may be compressed to save transmission bandwidth.

In another aspect, a monitoring system for a person includes one or more wireless nodes forming a wireless network; and a wearable appliance having a wireless transceiver adapted to communicate with the one or more wireless nodes; and a heartbeat detector coupled to the wireless transceiver. Embodiments may also include an accelerometer to detect a dangerous condition such as a falling condition and to generate a warning when the dangerous condition is detected.

Implementations of the above aspect may include one or more of the following. The wristwatch determines position based on triangulation. The wristwatch determines position based on RF signal strength and RF signal angle. A switch detects a confirmatory signal from the person. The confirmatory signal includes a head movement, a hand movement, or a mouth movement. The confirmatory signal includes the person's voice. A processor in the system executes computer readable code to transmit a help request to a remote computer. The code can encrypt or scramble data for privacy.

The processor can execute voice over IP (VOIP) code to allow a user and a remote person to audibly communicate with each other. The voice communication system can include Zigbee VOIP or Bluetooth VOIP or 802.XX VOIP. The remote person can be a doctor, a nurse, a medical assistant, or a caregiver. The system includes code to store and analyze patient information. The patient information includes medicine taking habits, eating and drinking habits, sleeping habits, or excise habits. A patient interface is provided on a user computer for accessing information and the patient interface includes in one implementation a touch screen; voice activated text reading; and one touch telephone dialing. The processor can execute code to store and analyze information relating to the person's ambulation.

A global positioning system (GPS) receiver can be used to detect movement and where the person falls. The system can include code to map the person's location onto an area for viewing. The system can include one or more cameras positioned to capture three dimensional (3D) video of the patient; and a server coupled to the one or more cameras, the server executing code to detect a dangerous condition for the patient based on the 3D video and allow a remote third party to view images of the patient when the dangerous condition is detected.

In another aspect, a monitoring system for a person includes one or more wireless bases; and a cellular telephone having a wireless transceiver adapted to communicate with the one or more wireless bases; and an accelerometer to detect a dangerous condition and to generate a warning when the dangerous condition is detected.

In yet another aspect, a monitoring system includes one or more cameras to determine a three dimensional (3D) model of a person; means to detect a dangerous condition based on the 3D model; and means to generate a warning when the dangerous condition is detected.

In another aspect, a method to detect a dangerous condition for an infant includes placing a pad with one or more sensors in the infant's diaper; collecting infant vital parameters; processing the vital parameter to detect SIDS onset; and generating a warning.

Advantages of these embodiments may include one or more of the following. The system for non-invasively and continually monitors a subject's arterial blood pressure, with reduced susceptibility to noise and subject movement, and relative insensitivity to placement of the apparatus on the subject. The system does not need frequent recalibration of the system while in use on the subject.

In particular, it allows patients to conduct a low-cost, comprehensive, real-time monitoring of their blood pressure. Using the web services software interface, the invention then avails this information to hospitals, home-health care organizations, insurance companies, pharmaceutical agencies conducting clinical trials and other organizations. Information can be viewed using an Internet-based website, a personal computer, or simply by viewing a display on the monitor. Data measured several times each day provide a relatively comprehensive data set compared to that measured during medical appointments separated by several weeks or even months.

This allows both the patient and medical professional to observe trends in the data, such as a gradual increase or decrease in blood pressure, which may indicate a medical condition. The invention also minimizes effects of white coat syndrome since the monitor automatically makes measurements with basically no discomfort; measurements are made at the patient's home or work, rather than in a medical office.

The wearable appliance is small, easily worn by the patient during periods of exercise or day-to-day activities, and non-invasively measures blood pressure can be done in a matter of seconds without affecting the patient. An on-board or remote processor can analyze the time-dependent measurements to generate statistics on a patient's blood pressure (e.g., average pressures, standard deviation, beat-to-beat pressure variations) that are not available with conventional devices that only measure systolic and diastolic blood pressure at isolated times.

Other advantages of the invention may include one or more of the following. The wearable appliance provides an in-depth, cost-effective mechanism to evaluate a patient's cardiac condition. Certain cardiac conditions can be controlled, and in some cases predicted, before they actually occur. Moreover, data from the patient can be collected and analyzed while the patient participates in their normal, day to-day activities.

In cases where the device has fall detection in addition to blood pressure measurement, other advantages of the invention may include one or more of the following. The system provides timely assistance and enables elderly and disabled individuals to live relatively independent lives. The system monitors physical activity patterns, detects the occurrence of falls, and recognizes body motion patterns leading to falls. Continuous monitoring of patients is done in an accurate, convenient, unobtrusive, private and socially acceptable manner since a computer monitors the images and human involvement is allowed only under pre-designated events.

The patient's privacy is preserved since human access to videos of the patient is restricted: the system only allows human viewing under emergency or other highly controlled conditions designated in advance by the user. When the patient is healthy, people cannot view the patient's video without the patient's consent. Only when the patient's safety is threatened would the system provide patient information to authorized medical providers to assist the patient. When an emergency occurs, images of the patient and related medical data can be compiled and sent to paramedics or hospital for proper preparation for pick up and check into emergency room.

The system allows certain designated people such as a family member, a friend, or a neighbor to informally check on the well-being of the patient. The system is also effective in containing the spiraling cost of healthcare and outpatient care as a treatment modality by providing remote diagnostic capability so that a remote healthcare provider (such as a doctor, nurse, therapist or caregiver) can visually communicate with the patient in performing remote diagnosis. The system allows skilled doctors, nurses, physical therapists, and other scarce resources to assist patients in a highly efficient manner since they can do the majority of their functions remotely.

Additionally, a sudden change of activity (or inactivity) can indicate a problem. The remote healthcare provider may receive alerts over the Internet or urgent notifications over the phone in case of such sudden accident indicating changes. Reports of health/activity indicators and the overall wellbeing of the individual can be compiled for the remote healthcare provider. Feedback reports can be sent to monitored subjects, their designated informal caregiver and their remote healthcare provider. Feedback to the individual can encourage the individual to remain active

. The content of the report may be tailored to the target recipient's needs, and can present the information in a format understandable by an elder person unfamiliar with computers, via an appealing patient interface. The remote healthcare provider will have access to the health and well-being status of their patients without being intrusive, having to call or visit to get such information interrogatively. Additionally, remote healthcare provider can receive a report on the health of the monitored subjects that will help them evaluate these individuals better during the short routine checkup visits. For example, the system can perform patient behavior analysis such as eating/drinking/smoke habits and medication compliance, among others.

Yet other advantages of the system may include one or more of the following. The patient's home equipment is simple to use and modular to allow for the accommodation of the monitoring device to the specific needs of each patient. Moreover, the system is simple to install. Regular monitoring of the basic wellness parameters provides significant benefits in helping to capture adverse events sooner, reduce hospital admissions, and improve the effectiveness of medications, hence, lowering patient care costs and improving the overall quality of care. Suitable users for such systems are disease management companies, health insurance companies, self-insured employers, medical device manufacturers and pharmaceutical firms.

The system reduces costs by automating data collection and compliance monitoring, and hence reduce the cost of nurses for hospital and nursing home applications. At-home vital signs monitoring enables reduced hospital admissions and lower emergency room visits of chronic patients. Operators in the call centers or emergency response units get high quality information to identify patients that need urgent care so that they can be treated quickly, safely, and cost effectively. The Web based tools allow easy access to patient information for authorized parties such as family members, neighbors, physicians, nurses, pharmacists, caregivers, and other affiliated parties to improved Quality of Care for the patient

In one embodiment with two or more cameras, camera parameters (e.g. field of view) are preset to fixed numbers. Each pixel from each camera maps to a cone space. The system identifies one or more 3D feature points (such as a birthmark or an identifiable body landmark) on the patient. The 3D feature point can be detected by identifying the same point from two or more different angles. By determining the intersection for the two or more cones, the system determines the position of the feature point. The above process can be extended to certain feature curves and surfaces, e.g. straight lines, arcs; flat surfaces, cylindrical surfaces. Thus, the system can detect curves if a feature curve is known as a straight line or arc. Additionally, the system can detect surfaces if a feature surface is known as a flat or cylindrical surface.

The further the patient is from the camera, the lower the accuracy of the feature point determination. Also, the presence of more cameras would lead to more correlation data for increased accuracy in feature point determination. When correlated feature points, curves and surfaces are detected, the remaining surfaces are detected by texture matching and shading changes. Predetermined constraints are applied based on silhouette curves from different views. A different constraint can be applied when one part of the patient is occluded by another object. Further, as the system knows what basic organic shape it is detecting, the basic profile can be applied and adjusted in the process.

In a single camera embodiment, the 3D feature point (e.g. a birth mark) can be detected if the system can identify the same point from two frames. The relative motion from the two frames should be small but detectable. Other features curves and surfaces will be detected correspondingly, but can be tessellated or sampled to generate more feature points. A transformation matrix is calculated between a set of feature points from the first frame to a set of feature points from the second frame. When correlated feature points, curves and surfaces are detected, the rest of the surfaces will be detected by texture matching and shading changes.

Each camera exists in a sphere coordinate system where the sphere origin (0,0,0) is defined as the position of the camera. The system detects theta and phi for each observed object, but not the radius or size of the object. The radius is approximated by detecting the size of known objects and scaling the size of known objects to the object whose size is to be determined.

For example, to detect the position of a ball that is 10 cm in radius, the system detects the ball and scales other features based on the known ball size. For human, features that are known in advance include head size and leg length, among others. Surface texture can also be detected, but the light and shade information from different camera views is removed. In either single or multiple camera embodiments, depending on frame rate and picture resolution, certain undetected areas such as holes can exist. For example, if the patient yawns, the patient's mouth can appear as a hole in an image. For 3D modeling purposes, the hole can be filled by blending neighborhood surfaces. The blended surfaces are behind the visible line

BRIEF DESCRIPTION OF THE DIAGRAM

FIG. 1: illustrates a pictorial representation of a remote monitoring system using (AI) Expert Systems wherein each new monitoring contact initiated by the healthcare practitioner with a known HMO patient is termed an "Encounter";

FIG. 2: illustrates pictorially a plurality of high risk patients being monitored using Al and DECvoice VAX 4000 located at a health plan facility;

FIG. 3: illustrates a schematic representation of the connections from a monitor/instrument at a patient's home to DECvoice through a telemedical interface box;

FIG. 4: schematically illustrates the circuit elements of an embodiment of a remote monitoring system using an expert system wherein Al may be built into an electronic programmable read only memory (EPROM), and using a dual-tone matrix frequency (DTMF) encoder;

FIGS. 5 and 6 illustrate examples of patient history data and other information which would be integrated into the system in order to enable meaningful and effective "parsing" during a patient encounter;

FIG. 7: illustrates a typical greeting which is parsed and tailored for encounter by a physician through a voice system, with a chosen home-bound (or depressed) patient or a high risk patient;

FIG. 8 illustrates examples of accompanying symptom questions which the voice system could pose to a home-bound/depressed patient;

FIG. 9: illustrates a new-problem questionnaire parsed for being presented in the physician's voice to the patient;

FIG. 10: illustrates a typical parsed message which will be presented to the patient in the doctor's own voice through the voice system at the conclusion of an encounter for monitoring.

FIG. 11: is an illustration of samples of WHY-NOT-MEDS-RULES, which are self explanatory, and can be made part of the artificial intelligence content to be used in the performance of the described system.

DESCRIPTION OF THE INVENTION

As illustrated, FIG. 1 shows a known HMO patient 101 whose condition will be monitored by the monitoring device, which, as aforesaid could take any form such as for example, blood pressure cuff, pulse monitor, uterine activity strips, glucometer or electroencephalograph (EEG) etc. If an infant is being remotely monitored, the illustrated embodiment will need to be modified to the extent that a "conversation" with the patient may not be practical, but the system would still function to enable and ensure timely intervention by a healthcare person or a physician.

As developed, an Al program directs the physician-patient conversation through voice technology, measuring physical parameters near the end of the conversation. The physician previously would have recorded questions typically asked during a patient examination; the Al program parses the questions and selects specific follow-up questions, depending upon the patient's responses. The automatic monitoring (note, the patient is not required to read the device) may take place at the end of the phone conversation, where the Al system commands the voice system to play the physician-recorded request to place the monitor in position, and the recording function takes place.

The patient monitoring device might use AT&T's Dual-Tone Matrix Frequency (DTMF) standard for touch-tone telephones, which DECvoice hardware (the Voice Synthesis/Recognition technology) can recognize. An inexpensive (less than $50.00) encoding device is used to translate the analog signal coming from the home monitoring instruments to the telephone. See FIG. 1.

The Artificial Intelligence system is driven by a simple to use Natural Language interface which directs the Voice system to send ("speak") appropriate questions, recognize ("listen for") the patient's answers, update the patient's database, direct the telephone-patient monitoring, and advises the HMO facility of critical patient conditions. The information acquired from the patient calls is available to the medical practitioner on both a real-time basis when the calls are being made, or on an ad-hoc basis after the calls are logged.

An example of the voice system which can be used in the present system is illustrated as VAX 4000 in FIG. 2 wherein artificial intelligence (AI) is pictorially illustrated as combined into the VAX 4000 unit. The two elements can be provided separately.

The Al element per se could take the form of an electronic programmable read only memory (EPROM) which could be programmed considering the physician's requirements and guidelines and also taking into account the requirements of the individual patient. The EPROM assists in "PARSING" the presentations to the patient which will be triggered/selected by the patient's response to a previous question. Examples of the "Parsing" used in the system are given hereinafter in conjunction with the explanation of FIGS. 5 through 10.

FIG. 3 illustrates schematically an arrangement which generates signals from monitored data to be sent to DECvoice for further processing. As shown, 301 represents an instrument at patient's home. In this context, it is to be understood that the patient is a patient in distress who would need continual monitoring and consequent timely intervention by a medical practitioner.

The instrument or device 301 illustrated schematically could take the form of any of several transducers encountered in patient monitoring, e.g., blood pressure cuff, pulse monitor, uterine activity strips, glucometer, electroencephalographs, etc., it being clearly understood that the patient is not required to read the instrument or device 301. Signals so generated by 301 are connected to a telemedical interface box 304 which functions in association with a telephone 302 without a modem. Functionally, the interface box 304 validates inputs, interpolates readings and generates dual-tone matrix frequency signals which are passed on to a remotely located DECvoice unit for further processing, over line 302.

FIG. 4 illustrates a high level schematic showing how monitored signals from an instrument/device at the patient's location can be conditioned encoded and converted into DTMF signals and passed on to a phone line for transmission to a remote location for being recorded, screened and analyzed on line.

A signal 401 received from an instrument, e.g., uterine activity strips, is sent through an optional operational amplifier at 402 if signal conditioning is required. Signals so conditioned are sent through a 4 bit A/D converter 403 and received by an input card 404. After performing the one out of 4 DTMF row selection and a one out of 4 DTMF column selection, the signals are processed through a DTMF encoder chip 405 which would take the form of an electronic programmable read only memory (EPROM). Examples of suitable EPROMS include Motorola MC 14410, AMI52559 and RCA CD 22951. Other EPROMS may equally be suitable.

FIG. 4 further illustrates schematically an arrangement which generates signals from monitored data to be sent to DECvoice for further processing. As shown, 401 represents an instrument at patient's home, the patient being a home-bound patient or a patient in distress who would need continual monitoring and consequent timely intervention by a medical practitioner.

The instrument or device 401 illustrated schematically corresponds to device 301 of FIG. 3 and could take the form of any of several transducers encountered in patient monitoring, e.g., blood pressure cuff, pulse monitor, uterine activity strips, glucometer, electroencephalographs, etc., it being clearly understood that the patient is not required to read the instrument or device 401. Signals so generated by 401 are connected to a telemedical interface box 404 which functions in association with a telephone 402 without a modem.

Functionally, the interface box 404 validates inputs, interpolates readings and generates dual-tone matrix frequency signals which are passed on to a remotely located DECvoice unit for further processing, over line 403. Typically, the DECvoice unit can simultaneously handle a plurality of lines which are limited only by the type of DECvoice unit used. A DECvoice unit capable of handling 48 lines simultaneously has been used in monitors which have already been designed. No serious limitations need exist on how many lines the DECvoice unit can accept for simultaneous handling. An example of a suitable DECvoice unit is the DECvoice 1 168 VAX System, described in the 1991 Digital Catalog entitled VAX Systems and DEC systems, Systems and Options Catalog 1991 October-December. This unit has the following capabilities:

(i) Digitized Voice

(ii) Speech Synthesis

(iii) Voice recognition and

(iv) touch tone capability whereby DTMF frequencies can be accepted, generated and detected.

In lieu of the DECvoice 1-168 unit, other commercially available units which functionally perform in a similar manner are equally acceptable.

In further reference to FIGS. 3 and 4, in addition to a first telephone line over which the patient will be presented the physician's questions and the patient will send his responses, a second telephone line in parallel with the first line is provided for transmission of signals from the monitoring device. The second telephone line includes the telemedical interface box 304 which could be a modem sized (--this is not a modem per se--) unit which houses certain hardware. Advantageously there may be jacks provided on the front of the interface box which jacks will be size keyed to various medical monitors the patient/user may have. Upon voice command (e.g., DECvoice) the user might plug in the required instrument or monitoring device (if it is not already plugged in) whereupon the reading-signal from the monitoring device is taken and DTMF encoded and transmitted to DECvoice.

Electronics inside the box might include a DTMF encoder, a 4-bit a/d converter with DE multiplexer to select 1 row and 1 column from the decimal 1 of 16 (since 4 bit) D/A, and any signal conditioning circuitry. There might be a DTMF decoder, which reads a touchtone emitted by DECvoice and decodes it, causing an LED to flash above the appropriate jack, and disabling other analog inputs, so that a valid reading is taken, DTMF exchanges can only occur "for" PROM-based ID of the box (i.e. patient), or encoded data (so the user hitting touchtone keys cannot generate a valid reading of their own).

Artificial Intelligence (Ai) And Parsing

In order that the described system should function as desired, patient information including patient data, medical history and other considerations relevant to the treatment of the patient concerned are recorded for use with the application of Al and parsing during telephone encounter with a patient to be monitored. Examples of such patient information to be recorded are illustrated in FIGS. 5 and 6. FIG. 7 shows a typical greeting which the voice system integrated into the monitoring system would present to a home-bound patient or a depressed patient represented as "dp-name".

Next could follow a question which the Al program would select from a choice typically illustrated in FIG. 8. Depending on and responsive to the patient's answers, the Al program will parse, i.e., match a question as in FIG. 9 with an appropriate selection from the right hand side listing. The encounter could continue through some more questions, each time the Al program parsing to match an unfilled portion of the question from several choices, based on the Al program and the patient's response.

In this context, mention may be made of what is known as a "Turing Test" originally published in 1950 by a British computer scientist Alan F. Turing. Turing's original criterion in 1950 was that even if seven out of ten persons, conversing with a voice system for five minutes on any subject mistook the computer for a human being, then the conclusion would be that there was behavioral evidence that the computer did use logic and was thinking. The Turing test standards appear to have somewhat changed now, but the concept remains. Experiments initially conducted with the monitoring system described herein have produced very encouraging results, and a significant percentage of people who were conversing with a voice-system using Al of this invention believed that they were conversing with a human being.

Claims (6)

WE CLAIM

1) Our Invention" IAS- Patients Monitoring System" is a method and system for remote monitoring of high-risk patients using artificial intelligence and a plurality of high-risk patients can be simultaneously monitored without patient intervention. The invention is a patient hears questions in the doctor's voice at each monitoring encounter and responds and the patient's responses are recorded at a remote central monitoring station and can be analyzed on line or later. The IAS- patients monitoring system is an artificial intelligence-Al and voice technology are combined to present to the patient during a monitoring session or encounter questions which would be selected from a plurality of different recorded questions. The invented system also includes the questions to the patient are chosen using Al, based on the patient's response by parsing and the monitor could take several forms such as for e.g., uterine activity strips, glucometers, blood pressure cuffs, pulse monitors, electroencephalographs, etc. Preferably, four telephone lines are dedicated to each patient. The invented system also includes one for the monitor, one for the voice, one as a backup and one to sense failures and dual tone matrix frequency signals may be used for transmission of monitored signals and other information which can be recognized by system which is but one example of the voice technology which can be used.

2) According to claims# the invention is to a method and system for remote monitoring of high-risk patients using artificial intelligence and a plurality of high-risk patients can be simultaneously monitored without patient intervention.

3) According to claiml,2# the invention is to a patient hears questions in the doctor's voice at each monitoring encounter and responds and the patient's responses are recorded at a remote central monitoring station and can be analyzed on line or later.

4) According to claiml,2# the invention is to an artificial intelligence-Al and voice technology are combined to present to the patient during a monitoring session or encounter questions which would be selected from a plurality of different recorded questions.

5) According to claiml,2,4# the invention is to the questions to the patient are chosen using Al, based on the patient's response by parsing and the monitor could take several forms such as for e.g., uterine activity strips, glucometers, blood pressure cuffs, pulse monitors, electroencephalographs, etc.

6) According to claim1,2,4,5# the invention is to the monitor, one for the voice, one as a backup and one to sense failures and dual tone matrix frequency signals may be used for transmission of monitored signals and other information which can be recognized by system which is but one example of the voice technology which can be used.

FIG. 1: ILLUSTRATES A PICTORIAL REPRESENTATION OF A REMOTE MONITORING SYSTEM USING (AI) EXPERT SYSTEMS WHEREIN EACH NEW MONITORING CONTACT INITIATED BY THE HEALTHCARE PRACTITIONER WITH A KNOWN HMO PATIENT IS TERMED AN "ENCOUNTER";

FIG. 2: ILLUSTRATES PICTORIALLY A PLURALITY OF HIGH RISK PATIENTS BEING MONITORED USING AI AND DECVOICE VAX 4000 LOCATED AT A HEALTH PLAN FACILITY.

FIG. 3: ILLUSTRATES A SCHEMATIC REPRESENTATION OF THE CONNECTIONS FROM A MONITOR/INSTRUMENT AT A PATIENT'S HOME TO DECVOICE THROUGH A TELEMEDICAL INTERFACE BOX.

FIG. 4: SCHEMATICALLY ILLUSTRATES THE CIRCUIT ELEMENTS OF AN EMBODIMENT OF A REMOTE MONITORING SYSTEM USING AN EXPERT SYSTEM WHEREIN AI MAY BE BUILT INTO AN ELECTRONIC PROGRAMMABLE READ ONLY MEMORY (EPROM), AND USING A DUAL-TONE MATRIX FREQUENCY (DTMF) ENCODER.

FIG. 5: ILLUSTRATE EXAMPLES OF PATIENT HISTORY DATA AND OTHER INFORMATION WHICH WOULD BE INTEGRATED INTO THE SYSTEM IN ORDER TO ENABLE MEANINGFUL AND EFFECTIVE "PARSING" DURING A PATIENT ENCOUNTER;

FIG. 6: ILLUSTRATE EXAMPLES OF PATIENT HISTORY DATA AND OTHER INFORMATION WHICH WOULD BE INTEGRATED INTO THE SYSTEM IN ORDER TO ENABLE MEANINGFUL AND EFFECTIVE "PARSING" DURING A PATIENT ENCOUNTER.

FIG. 7: ILLUSTRATES A TYPICAL GREETING WHICH IS PARSED AND TAILORED FOR ENCOUNTER BY A PHYSICIAN THROUGH A VOICE SYSTEM, WITH A CHOSEN HOME-BOUND (OR DEPRESSED) PATIENT OR A HIGH RISK PATIENT;

FIG. 8: ILLUSTRATES EXAMPLES OF ACCOMPANYING SYMPTOM QUESTIONS WHICH THE VOICE SYSTEM COULD POSE TO A HOME-BOUND/DEPRESSED PATIENT;

FIG. 9: ILLUSTRATES A NEW-PROBLEM QUESTIONNAIRE PARSED FOR BEING PRESENTED IN THE PHYSICIAN'S VOICE TO THE PATIENT.

FIG. 10: ILLUSTRATES A TYPICAL PARSED MESSAGE WHICH WILL BE PRESENTED TO THE PATIENT IN THE DOCTOR'S OWN VOICE THROUGH THE VOICE SYSTEM AT THE CONCLUSION OF AN ENCOUNTER FOR MONITORING.

FIG. 11: IS AN ILLUSTRATION OF SAMPLES OF WHY-NOT-MEDS-RULES, WHICH ARE SELF-EXPLANATORY, AND CAN BE MADE PART OF THE ARTIFICIAL INTELLIGENCE CONTENT TO BE USED IN THE PERFORMANCE OF THE DESCRIBED SYSTEM.