Posts Tagged ‘Mohan Singh’

Supporting the Transition from Hospital to Home for Premature Infants… - May 23rd, 2011

Moleskins and Pens

Photo courtesy of paulworthington

Congratulations to Informatics faculty members Gillian Hayes and Don Patterson, their collaborator Mohan Singh (in Ireland!), and UCI medical school faculty, students and staff, Dan Cooper, Dana Gravem and Julia Rich on having their paper,
‘Supporting the Transition from Hospital to Home for Premature Infants Using Integrated Mobile Computing and Sensor Support’ accepted to Personal and Ubiquitous Computing (Springer journal).

Abstract: This paper reports on the requirements for, design of, and preliminary evaluation of a novel pervasive healthcare system for supporting the care of premature infants as they transition from hospital to home. In support of this system, we report the results of gesture sensing in a clinical setting and of interviews and focus groups with caregivers and clinicians who are involved in the post natal transition to the home. From these results, we developed prototype systems for monitoring and tracking observations of behavioral and health-related data in the home, including both a mobile-phone based capture and access system for caregivers, a sensing platform and an activity-recognition algorithm for automatically documenting infant movement. We describe the results of preliminary trials of both systems with an emphasis on the synergistic importance of bridging this transition. The results of these trials indicate that clinically relevant monitoring can be accomplished in the home, but there is still more to do to integrate these approaches into a comprehensive monitoring system for this population.

Tags: , , , , , , , , , , , ,
Posted: 5/23/11 9:00 am UTC by Make the First Comment
GD Star Rating
loading...

LUCI is doing: FitBaby: Hospital to Home - May 9th, 2011

FitBaby: Hospital to Home

FitBaby: Hospital to Home

What has LUCI been up to recently?

FitBaby: Hospital to Home

Premature birth is associated with long term health impairments including neurological and cognitive deficiencies, chronic lung disease, and altered growth patterns of lean, fat, and bone tissues. Furthermore, parents of premature infants may experience excessive stress, post-partum depression, and other challenges associated with the birth of and caring for their child. We are designing, developing, and deploying technologies to detect abnormal baby movements in the NICU with accelerometers. Data collection continues as these high risk babies move home with a mobile solution for collecting infant and caregiver observations, sharing this data with their providers, and visualizing and summarizing these data. We are additionally developing a capture and access tool called Estrellita to share data with healthcare providers, close relatives, and friends.

More info

Tags: , , , , , , , , , , , ,
Posted: 5/9/11 10:00 am UTC by Make the First Comment
GD Star Rating
loading...

Involuntary Gesture Recognition for Predicting Cerebral Palsy in High-Risk Infants - July 21st, 2010

Moleskins and Pens

Photo courtesy of paulworthington

Congratulations to former Informatics visiting scholar Mohan Singh and Informatics Faculty Member Donald J. Patterson on having their paper accepted to the IEEE International Symposium on Wearable Computers
‘Involuntary Gesture Recognition for Predicting Cerebral Palsy in High-Risk Infants’

Abstract:In this paper we describe a system that leverages accelerometers to recognize a particular involuntary gesture in babies that have been born preterm. These gestures, known as cramped-synchronized general movements, have been shown to be highly correlated with a diagnosis of Cerebral Palsy. In order to test our system we recorded data from 10 babies admitted to the newborn intensive care unit at the UCI Medical Center. We applied machine learning techniques to features based on their data and were able to obtain high accuracies on this cohort. Validated video observation annotations were utilized as ground truth. Finally, we conducted an analysis to understand the basis of the algorithmic predictions.

Congratulations Mohan, and Don!

Tags: , , , , , , , , , ,
Posted: 7/21/10 3:59 pm UTC by Make the First Comment
GD Star Rating
loading...