57 results about "Patient behavior" patented technology

This present disclosure relates to systems and methods for providing an Adaptive Analytical Behavioral and Health Assistant. These systems and methods may include collecting one or more of patient behavior information, clinical information, or personal information; learning one or more patterns that cause an event based on the collected information and one or more pattern recognition algorithms; identifying one or more interventions to prevent the event from occurring or to facilitate the event based on the learned patterns; preparing a plan based on the collected information and the identified interventions; and / or presenting the plan to a user or executing the plan.

A method and apparatus is disclosed for providing a virtual environment or a visual presentation to a user. A portion of interest is created and depending on a response of the user to the virtual environment or to the visual presentation, a feedback is preferably provided.

Systems and methods for identifying, monitoring, influencing and rewarding positive healthcare behavior are provided. The method and system includes a device receiving patient specific data which include patient care indicators associated with the patient. The device compares the patient specific data against a database that relates each patient care indicator with at least one patient care module. The device generates customized patient care plan that includes patient care modules. The patient specific data also includes one or more compliance indicators, indicating the patient's interactions with the patient care modules. The device assesses patient behavior based on the compliance indicator. A reward is issued to a patient on a condition that the patient adheres to the customized patient care plan

An interactive home treatment system and method is disclosed. Patient data is collected via a handheld device and stored in a database. The data may be related to self-treatments, symptoms, or patient behavior. The data are analyzed with an analytic tool and the analysis is used to generate a message that is transmitted to a treating health care professional or to the patient, or both. A set of predetermined rules may be applied to the data. The rules may be modified by the treating health care professional, the patient, or both. The handheld device, the database, and the analytic tool may be web-enabled to facilitate communication from virtually anywhere.

An interactive home treatment system and method is disclosed. Patient data is collected via a handheld device and stored in a database. The data may be related to self-treatments, symptoms, or patient behavior. The data are analyzed with an analytic tool and the analysis is used to generate a message that is transmitted to a treating health care professional or to the patient, or both. A set of predetermined rules may be applied to the data. The rules may be modified by the treating health care professional, the patient, or both. The handheld device, the database, and the analytic tool may be web-enabled to facilitate communication from virtually anywhere.

Systems, methods and apparatus are provided through which in some embodiments detection of a change in characteristics of plaque in a longitudinal exam is automated for the purpose of assessing change in disease due to therapy, patient behavior modifications or follow-up. In some embodiments, diagnosis and treatment of arterial lesions includes obtaining a plurality of sets of computed-tomography images of at least one arterial plaque lesion, wherein each set of computed-tomography images are acquired at a different time, then storing the computed-tomography images in a database and analyzing arterial plaque variations in the sets of computed-tomography images for changes in at least one parameter.

Systems and methods are provided for managing medical adherence. An exemplary method may include managing medical adherence utilizing data aggregating and processing to determine impact on a user's health based on their behavior related to prescribed medication. The method may entail utilizing data related to a medication regimen and patient behavior to determine a patient's compliance to the regimen in terms of dosage and time. These values may be utilized to calculate a medical adherence value representing a patient's adherence to a prescribed regimen. Responsive to determining low medical adherence, a notification may be generated which may result in an intervention with the patient.

This present disclosure relates to systems and methods for providing an Adaptive Analytical Behavioral and Health Assistant. These systems and methods may include collecting one or more of patient behavior information, clinical information, or personal information; learning one or more patterns that cause an event based on the collected information and one or more pattern recognition algorithms; identifying one or more interventions to prevent the event from occurring or to facilitate the event based on the learned patterns; preparing a plan based on the collected information and the identified interventions; and / or presenting the plan to a user or executing the plan.

The invention provides improved methods for analysis of data obtained from certain pulmonary testing procedures, in particular from whole body plethysmography or from the forced oscillation technique. The improved computer-implemented methods automatically recognize data that has been distored by patient behaviors during testing. This invention also provides computer systems that interface to devices that perform whole body plethysmography and / or the forced oscillation technique and automatically execute the methods of this invention. This invention also provides for distribution of software that causes computer systems to perform the methods of this invention.

The invention belongs to the technical field of autism rehabilitation, and particularly relates to an autism rehabilitation education man-machine interaction intensive training system. The training system comprises a remote server, and an intelligent helmet, intelligent gloves, a human body wearing suit and a doctor terminal which are in communication with the remote server. The intelligent helmet, the intelligent gloves and the human body wearing suit are used for collecting behavior information of a patient and feeding the behavior information of the patient back to the remote server. The remote server is used for analyzing behaviors and moods of the patient according to the behavior information of the patient and a historical file of the patient, controlling the intelligent gloves and the human body wearing suit to conduct vibrating massage on the patient and controlling the intelligent helmet to play voice and VR images, thereby conducting guiding treatment and rehabilitation training on the patient. Through the behavior information collected in real time of the patient and the historical file of the patient, the patient is analyzed, then guiding treatment and rehabilitation training are conducted on the patient, and compared with traditional artificial treatment, the treatment efficiency is improved and a better treatment effect is achieved.

System and method for monitoring a patient's health condition is disclosed. The system assesses the patient's health condition based on a data collected by observing the physical activity of the patient and the physical state of the patient. The physical state is measured by vital sign measuring sensors. The patient's health condition is assessed by the system by collectively analyzing the physical activity, the physical state, and a correlation among the acquired data. Further, an authorized personnel issues an intervention to interact with the patient and to validate the assessment of the patient's health condition.

The invention discloses an intelligent medical service robot capable of achieving biological feedback and remote visiting. The robot comprises a robot body, a control module, a communication module, avisual perception module, an omni-directional moving module, an SLAM mapping navigation module, a temperature measuring module, a disinfecting module and a voice and video module, the control moduleis connected with and controls the visual perception module, the omni-directional moving module, the SLAM mapping navigation module, the temperature measuring module, the disinfecting module, the communication module and the voice and video module, the visual perception module is provided with a depth camera, the depth camera is connected with the control module, the control module is in wirelessconnection with a mobile terminal of relatives of patient through the communication module, the control module is used for triggering the voice and video module to carry out language reminding under the condition that the patient behavior is abnormal, diagnosis and treat are finished, or the patient temperature is abnormal, and under the condition that the patient mood needs to be pacified, the voice and video module is triggered to carry out mood pacifying, biological feedback and remote visiting can be achieved, and the robot has the higher man-machine interactive capacity and the intelligence level.

The embodiment of the invention discloses a patient activity analysis system and method for behavior recognition based on a wearable device. The system comprises an acceleration sensor, a patient client, a data collection unit, a database server, a computing server and a doctor client, wherein the acceleration sensor is used for acquiring patient behavior information data; the patient client is used for acquiring patient personal information and performing feature selection on the obtained patient behavior information; the data collection unit is used for collecting the acquired patient behavior information and personal information and performing extraction and computation processing on the patient behavior information; the database server is used for storing a patient personal informationand daily behavior information record; the computing server is used for performing computational recognition processing on patient behavior information data; the doctor client is used for querying the patient behavior record according to a patient visit number. In the embodiment of the invention, the problem that a doctor knows patient daily activities difficultly can be solved, and the doctor can make evaluation according to the patient daily activities; a patient can conveniently view personal history activity data and get advices from their doctors.

The present disclosure relates to the reduction of pressure ulcers and falls with respect to patients with physical or cognitive impairments who are in bed. A control system assures that the bed and ancillary apparatus are physically set and that patient behaviors are responded to by care providers. Motion is monitored with a non-mutually exclusive portfolio of sensors, and this information is used by one or more reasoning engines. An integrated clinical workflow is informed by the patterns of movement and then the physical environment, patient interaction, and care provider workflow are controlled to reduce the incidence of falls and pressure ulcers in bed ridden patients.

The invention discloses a hospital medicine distribution method based on a patient behavior trajectory. Firstly, the basic requirement is predicated according to historical sales data of medicine so as to configure an initial inventory, medicine is supplemented before the work time of a hospital, and the medicine is allocated to all layers of pharmacies of the hospital; during the work time of the hospital, the dynamic required medicine amount is predicated in real time according to the patient behavior trajectory, and medicine supplement and medicine allocation are conducted on all layers of the pharmacies timely, so that the patient behavior trajectory information is effectively utilized to reduce medicine shortage or inventory redundancy caused by dynamic medicine requirement fluctuation. The medicine requirement of the pharmacies in the hospital can be better met, and unification of logistics, information stream, capital flow and service flow under the drive of the patient behavior trajectory is achieved in the process that the requirements of patients are met.

A structure, method, and computer program product for a diabetes control system provides, but is not limited thereto, the following: open-loop or closed-loop control of diabetes that adapts to individual physiologic characteristics and to the behavioral profile of each person. An exemplary aspect to this adaptation is biosystem (patient or subject) observation and modular control. Consequently, established is the fundamental architecture and the principal components for a modular system, which may include algorithmic observers of patients' behavior and metabolic state, as well as interacting control modules responsible for basal rate, insulin boluses, and hypoglycemia prevention.

The invention relates to the technical field of digital medical treatment, and discloses a clinical path mining method and device, equipment and a storage medium, and the method comprises the steps: obtaining to-be-analyzed clinical data of a target disease, the to-be-analyzed clinical data being clinical data obtained according to the historical clinical data of a plurality of patients corresponding to the target disease; carrying out matrix construction on the clinical data to be analyzed to obtain a clinical data matrix to be analyzed; clustering patient behaviors of the clinical data matrix to be analyzed according to charging items to obtain a patient behavior set corresponding to the clinical data to be analyzed; carrying out patient behavior matching and replacement on the charging items of the to-be-analyzed clinical data by adopting the patient behavior set to obtain a clinical patient behavior sequence corresponding to the to-be-analyzed clinical data; and performing time sequence frequent set mining according to the clinical patient behavior sequence to obtain a plurality of target clinical paths corresponding to the target disease. Therefore, the flexibility and interpretability of the clinical path obtained by mining are improved.

The invention relates to a patient behavior multimodal analysis and prediction system based on statistical learning. The system comprises a multimodal acquisition module, a posture-based patient behavior recognition module, a physiological signal-based patient behavior recognition module, an emotion signal-based patient behavior recognition module, a voice signal-based patient behavior recognitionmodule and a multi-kernel learning-based fusion module. The multi-kernel learning-based fusion module comprises a multi-kernel classifier, and the training process of the multi-kernel learning-basedfusion module specifically comprises the steps that all kernel functions are trained and combined, then overall training is conducted, and the weight coefficient of each kernel function is obtained. Compared with the prior art, according to the invention, the applied multimodal data is closer to the real form of the patient information flow under the background of cloud computing and big data, hascomprehensiveness and complexity, reduces the loss of a large amount of information when facing complex nonlinear multi-modal information processing by utilizing the multi-feature multi-core learningmethod, and has better performance when processing data with larger modal span.

The invention relates to a patient behavior multi-modal perception and analysis system based on deep learning. The patient behavior multi-modal perception and analysis system comprises a data acquisition unit, a patient human body posture recognition unit, a patient physiological signal recognition unit, a patient image information recognition unit, a patient voice information recognition unit anda deep fusion unit, preprocessing and interested area extraction and diagnosis are achieved on collected multi-modal data such as postures, physiology, images and voice of patients, a deep fusion unit adopts a multi-modal two-dimensional feature and three-dimensional feature fusion network structure, and a preliminary segmentation result is obtained through a 2D deep learning network; and a patient behavior detection result is acquired on the basis of the preliminary segmentation result through a 3D deep learning network. Compared with the prior art, the invention has the advantages that thepatient behavior is evaluated more accurately, the focus is accurately positioned, the accuracy of predicting the pathological trend of the patients are remarkably improved, and a powerful basic guarantee is provided for implementation of scientific intervention of the patient behavior and intelligent optimization means of a medical process.

A patient monitoring system with image capture functionality, wherein the system is configured such that image data is recorded in response to the sensor signal only if that sensor signal is generated more than a predefined period of time following the identification of a predefined access token. Methods for operating such a system, and computer software / hardware configured to enable the operation and / or configuration of such a system are also disclosed. The embodiments described herein are designed in particular, to assist in protecting a patient against unauthorized persons attempting to interfere with the patient. The system has other management functions such as analyzing fall risk likelihoods, observing patient behavior, improving staff response times, statistical analysis, and ascertaining false alarms

The invention belongs to the technical field of probiotics, and more specifically discloses probiotics capable of improving symptoms of patients with autism spectrum disorders. The probiotics capableof improving symptoms of patients with autism spectrum disorders are composed of Lactobacillus bulgaricus, Bifidobacterium infantis, Bifidobacterium longum, Bifidobacterium bifidum, Lactobacillus acidophilus, and Lactobacillus casei at a mass ratio of 1-6:2-7:2-5:1-3:0.8-2.5:0.5-2. According to a preparation method, microbiome-gut-brain axis effect mechanism is adopted, a scientific ratio is adopted, so that that probiotics capable of improving symptoms of patients with autism spectrum disorders are prepared. The probiotics are capable of improving the core symptoms of patients with autism spectrum disorders, the autism spectrum disorder patient behavior improvement rate is 80%, the constipation improvement rate is 80%, the diarrhoea improvement rate is 40%, the emotion improvement rate is21%, the diet improvement rate is 16%, and the sleep quality improvement rate is 12%.

Systems and methods are provided for managing medical adherence. An exemplary method may include managing medical adherence utilizing data aggregating and processing to determine impact on a user's health based on their behavior related to prescribed medication. The method may entail utilizing data related to a medication regimen and patient behavior to determine a patient's compliance to the regimen in terms of dosage and time. These values may be utilized to calculate a medical adherence value representing a patient's adherence to a prescribed regimen. Responsive to determining low medical adherence, a notification may be generated which may result in an intervention with the patient.

Systems and methods are disclosed for presenting medical treatment information relating to a patient's conditions or symptoms. Some embodiments of the system include interactive display views presenting patient behavioral instructional information in multiple formats, including, for example, textual and / or multimedia. Some embodiments of the system can present information such as, for example, guidance on how to administer and / or receive one or more medical treatments. Information presented can, in part, be determined by logical processing of information obtained interactively from a patient, patient's assistance, biometric data collection device, and / or medical practitioner. The system can log session navigation and data collection information to a local data store and / or transmit that information to a remote device for additional processing and / or storage. In one embodiment, the system provides behavior based birthing assistance.

Gastric stimulation systems and methods are provided for treating a patient, particularly by modifying behavior of the patient leading to excess weight loss. In some embodiments, such weight loss is achieved with a combination approach which includes two or more of the following: acute screening of the potential patients, gastric stimulation, induction of symptoms or specific behaviors and integration of patient management data into the treatment plan. Gastric stimulation is provided to portions of the gastrointestinal tract, particularly the stomach, with the use of at least one electrode. A variety of gastric stimulation systems may be used, including stimulators that are endoscopically placed, laparoscopically placed or placed by modified or combination methods.

A method for behavior monitoring using a wearable detector is described. The method includes detecting a force of a patient action using the detector worn by the patient. The patient action is characterized as a behavior based on a location of the detector; and a frequency of the force, a magnitude of the force, a direction of the force and / or one or more threshold values. A determination is made as to whether to transmit a notification based at least in part on the behavior characterized. In response to a determination to transmit a notification, the notification is transmitted. Apparatus and computer readable media are also described.

The invention discloses a rare disease auxiliary analysis method based on artificial intelligence. The method comprises the following steps of: obtaining a rare patient behavior log in a log source; extracting related features of a rare patient in the rare patient behavior log; performing similarity comparison on the related features of the rare patient and rare patient feature vectors in a rare patient feature library, and selecting the rare patient feature vector with the highest similarity as the feature vector of the rare patient; pushing a corresponding treatment scheme to the rare patient according to the feature vector of the rare patient; and conducting clustering analysis on the feature vector of the rare patient, and adding the feature vector of the rare patient to a corresponding position of a group feature library according to the clustering analysis result. According to the method, the group feature library can be perfected, a rare disease knowledge database can be established, the behaviors of a user can be analyzed, a corresponding treatment scheme can be pushed to the user according to the analysis result, and the problems of rare disease patient multivariate heterogeneous data storage and automatic analysis are solved.

Systems, devices, and methods are provided that allow detection of episodes in analyte measurement, prompting a patient to self-report possible causes for the episodes. Correlation of possible causeswith detected episodes assists patient behavior modification to reduce the occurrence of episodes.

A method of detecting fraudulent patient behavior in a clinical research study includes receiving, at a computing device, a patient fingerprint image, from an imaging device of administrator or investigator computing device; comparing, at the computing device, the received patient fingerprint image to a database of existing patient fingerprint images to determine if the patient is previously enrolled in a clinical study; communicating a message identifying the patient may be eligible to enroll if no match is found between the received fingerprint image and the database of existing patient fingerprint images; and performing additional analysis with respect to the patient if a match is found between the received fingerprint image and the database of existing fingerprint images.

The invention relates to the technical field of child behavior monitoring, in particular to a behavior monitoring and reminding correction system for children hyperactivity disorder patients. The system comprises a correction table, a correction chair and a rewarding device and further comprises a detection reminding module, the detection reminding module is electrically connected to a central processing module, the central processing module comprises a time delay unit, the detection reminding module comprises a detection unit and a voice broadcasting unit, the voice broadcast unit is electrically connected to the central processing module, the rewarding device comprises a rewarding box, a conveying groove is formed in the rewarding box, a conveying rod is slidably arranged in the conveying groove in the vertical direction, a starting assembly is arranged in the rewarding box, candies are placed on the upper surface of the conveying rod, a discharging groove is formed above the conveying groove, one end of the discharging groove is communicated with the conveying groove, a discharging port is formed in the other end of the discharging groove, a discharging block is slidably arranged on the discharging groove in the length direction of the discharging groove, and a driving assembly is arranged on the rewarding box and connected to the starting assembly. The system can improve the hyperactivity habit of patients.

A system and method providing virtual physical rehabilitation services to a patient in the context of automated patient healthcare delivery is disclosed. The system / method are controlled by a patient healthcare plan (PHP) deployed from a host computer system (HCS) that triggers execution of a video script dataset (VSD) to coordinate presentation to a patient of rehabilitation audio / video information (AVI) derived from a video database (VDB). A mobile user device (MUD) executes the PHP autonomously to coordinate AVI display on a video display unit (VDU) for patient presentation. Patient reactions to the AVI are observed by a video imaging unit (VIU). An operator interface computer (OIC) communicates with the HCS and MUD permitting visualization of the VIU and AVI information by a healthcare provider and allowing observed patient behavior to be synchronously scored / logged / stored in a patient history database (PHD) by the HCS.