Clearcare, Inc.

Ricoh Company, Ltd.

Other

Clearshift Corporation

Geoffrey Nudd

Jonathan J Hull

David Cristman

Stephen Weyl

John Taylor

Peter E Hart

Jamey Graham

Berna Erol

Bala Krishna Nakshatrala

Sarah Cook

Kurt W Piersol

Michael J Gormish

Martin P Boliek

Bradley J Rhodes

Stephen R Savitzky

Kevin Ridout

Daniel J Elenbaas

Rajesh Krishnan

A system collects information associated with the work performance and work satisfaction of caregiver's who provide in-home care services to seniors. A machine learning system is trained to predict caregiver attrition and generate a user interface display indicative of a risk an individual caregiver will attrit. The system may also be used to determine action steps to reduce the risk of attrition of a caregiver.

Machine learning system and method for predicting caregiver attrition

The present disclosure describes a conversation facilitation system for facilitating conversation-based social interactions to improve senior health, one or more operations and functions being efficiently achieved via this system comprise: receiving a dialog act of a conversation, applying natural language understanding (NLU) processing on the dialog act, computing a conversation metric, and generating a result of the conversation to conclude the conversation based on the conversation metric.

Conversation facilitation system for mitigating loneliness

The in-home care of seniors is augmented using Internet of Things (IOT) technologies. In-home sensors monitor a senior and their caregiver. Physical conditions and psychological conditions may be monitored. In some implementations, a machine learning system has a classifier trained to detect a specified condition, such as depression. The system may perform various transformations of raw sensor data into a format indicative of a particular condition. In one implementation, a psychological or medical condition has symptoms in which each symptom has one or more measurable events. Mappings between symptoms, events, sensor data, and sensor transformation functions may be supported.

Automatic in-home senior care system augmented with internet of things technologies

The present disclosure describes a system to use conversation data of patients to detect dangerous mental or physical conditions, such as suicidal thoughts, physical abuse, recent falls, and viral infection. A machine learning system may be trained to identify a dangerous mental or physical condition from conversations based on examples of patients evaluated to have a specific mental or physical condition. Conversations of patients may be monitored, natural language understanding (NLU) processing performed, and a machine learning system used to detect dangerous mental or physical conditions.

Conversation system for detecting a dangerous mental or physical condition

A machine learning system passively monitors sensor data from the living space of a patient. The sensor data may include audio data. Audio features are generated. A trained machine learning model is used to detect a change in condition. In some implementations, the machine learning model is trained in a learning phase based on training data that includes questionnaires completed by caregivers and identified audio features.

Automatic change in condition monitoring by passive sensor monitoring and machine learning

An online work management system provides a marketplace for multiple job owner and workers. The job owners provide a job description that defines task. The job description may be processed to generate task descriptions that may be published for workers' application. The task descriptions specify the qualification or restrictions for workers to have the task assigned. The online work management system also provides various functions supporting coordination and management of task assignment such as determining the trust level of the user's identity, search the tasks or workers, monitoring the progress of job, managing payment to workers, training and testing the workers, evaluating the review by the job owners, and generation of surveys.

Trust level based task assignment in an online work management system

A telephony accessible calendar system is provided for use in a home care scheduling system for scheduling multiple daily work shifts of home care providers that includes a scheduling to organize work shifts of remote operating home care workers and confirmation to obtain an electronic signature from one or more persons operating as individual signers near the end of a work shift.

System for updating a calendar or task status in home care scheduling via telephony

Method and apparatus for recording associations with logs are described. In one embodiment, the method comprises obtaining a first media identifier corresponding to a first media; accessing a log that contains one or more entries that associate two or more media identifiers with each other; and determining that the first media is related to a second media based on the log indicating that a second media identifier is associated with, but different from, the first media identifier.

Method and apparatus for recording associations with logs

A Mixed Media Reality (MMR) system and associated techniques are disclosed. The MMR system provides mechanisms for forming a mixed media document that includes media of at least two types (e.g., printed paper as a first medium and digital content and/or web link as a second medium). In one embodiment, an MMR document is retrieved based on recognition of a paper document. Responsive to the comparison of the paper document and the virtual multimedia document, an action is performed. For example, the media of the matching MMR document can be displayed, or an action associated with the matching MMR document can be performed.

Growing community of inventors

San Francisco, CA, United States of America

Geoffrey Nudd