IBM Research and Rice University have collaborated to create the prototype IBM Multi-Purpose Eldercare Robot Assistant (IBM MERA), a Watson-enabled application designed to aid the elderly and assist caregivers. Watson is a question-answering computer system developed by IBM.

To help improve care of the elderly, IBM has opened an “Aging in Place” environment in its ThinkLab in Austin, Texas—where IBM MERA resides—that is designed to mimic the types of interactions elderly people have in their homes. Here, IBM studies how data from atmospheric, motion, audio and olfactory sensors could be used by caregivers to improve health care and wellness as physical or environmental conditions change.

Rice University PhD student George Chen (r) has his heart and respiratory rates measured by IBM MERA as IBM Research staff member Jinho Lee looks on. Image credit: Jack Plunkett/Feature Photo Service for IBM.IBM created the prototype robot with students and faculty from Rice’s psychology and electrical and computer engineering departments. The robot will be used to perform several tasks: helping study innovative ways of measuring an individual’s vital signs, such as heart and respiratory rates; answering basic health-related questions; and determining whether an individual has fallen by reading the results of an accelerometer.

IBM MERA runs on the IBM Cloud and a Softbank Pepper robot interface and uses IBM Watson technologies and CameraVitals—a technology developed in Rice’s Scalable Health Labs by Ashutosh Sabharwal, professor of electrical and computer engineering, and Ashok Veeraraghavan, assistant professor of electrical and computer engineering—which calculates vital signs by recording video of a person’s face. The labs specialize in developing continuous, passive and automatic sensors to simultaneously measure biological and behavioral markers, such as vital signs and blood perfusion.

These technologies allow IBM MERA to obtain fast, noninvasive readings on a patient’s heart and breathing measurements that can be performed multiple times per day. Combined with IBM Watson Speech to Text and Text to Speech applications, the camera can also view whether a fall has occurred and provide information for caregivers.

IBM MERA is also designed to interact with individuals using IBM Watson Speech to Text, Text to Speech and Natural Language Classifier applications so that researchers can study how they could receive answers to health-related questions, such as “What are the symptoms of anxiety?” and “What is my heart rate?”