A Wearable Wrist Band-Type System for Multimodal Biometrics Integrated with Multispectral Skin Photomatrix and Electrocardiogram Sensors.

Multimodal biometrics are promising for providing a strong security level for personal authentication, yet the implementation of a multimodal biometric system for practical usage need to meet such criteria that multimodal biometric signals should be easy to acquire but not easily compromised. We developed a wearable wrist band integrated with multispectral skin photomatrix (MSP) and electrocardiogram (ECG) sensors to improve the issues of collectability, performance and circumvention of multimodal biometric authentication. The band was designed to ensure collectability by sensing both MSP and ECG easily and to achieve high authentication performance with low computation, efficient memory usage, and relatively fast response. Acquisition of MSP and ECG using contact-based sensors could also prevent remote access to personal data. Personal authentication with multimodal biometrics using the integrated wearable wrist band was evaluated in 150 subjects and resulted in 0.2% equal error rate ( EER ) and 100% detection probability at 1% FAR (false acceptance rate) ( PD . 1 ), which is comparable to other state-of-the-art multimodal biometrics. An additional investigation with a separate MSP sensor, which enhanced contact with the skin, along with ECG reached 0.1% EER and 100% PD . 1 , showing a great potential of our in-house wearable band for practical applications. The results of this study demonstrate that our newly developed wearable wrist band may provide a reliable and easy-to-use multimodal biometric solution for personal authentication.

Multifactorial intervention in diabetes care using real-time monitoring and tailored feedback in type 2 diabetes.

AIMS: In 2011, we demonstrated that an individualized health management system employing advanced medical information technology, designated ubiquitous (u)-healthcare, was helpful in achieving glycemic control without hypoglycemia in patients with diabetes. Following this, we generated a new multidisciplinary u-healthcare system by upgrading our clinical decision support system (CDSS) rule engine and integrating a physical activity-monitoring device and dietary feedback into a comprehensive package. METHODS: In a randomized, controlled clinical trial, patients with type 2 diabetes aged over 60 years were assigned randomly to a self-monitored blood glucose (SMBG) group (N = 50) or u-healthcare group (N = 50) for 6 months. The primary endpoint was the proportion of patients achieving glycated hemoglobin (HbA1c) <7 % without hypoglycemia. Changes in body composition and lipid profiles were also investigated. The u-healthcare group was educated to use a specially designed glucometer and an activity monitor that automatically transferred test results to a hospital-based server. An automated CDSS rule engine generated and sent patient-specific messages about glucose, diet, and physical activity to their mobile phones and a Web site. RESULTS: After 6 months of follow-up, the HbA1c level was significantly decreased in the u-healthcare group [8.0 ± 0.7 % (64.2 ± 8.8 mmol/mol) to 7.3 ± 0.9 % (56.7 ± 9.9 mmol/mol)] compared with the SMBG group [8.1 ± 0.8 % (64.9 ± 9.1 mmol/mol) to 7.9 ± 1.2 % (63.2 ± 12.3 mmol/mol)] (P < 0.01). The proportion of patients with HbA1c < 7 % without hypoglycemia was greater in the u-healthcare group (26 %) than in the SMBG group (12 %; P < 0.05). Body fat mass decreased and lipid profiles improved in the u-healthcare group but not in the SMBG group. CONCLUSION: This u-healthcare service provided effective management for older patients with type 2 diabetes (ClinicalTrial.Gov: NCT01137058).

A Survey on Ubiquitous Healthcare Service Demand among Diabetic Patients.

BACKGROUND: Advanced information technology can be used when developing diagnostic and treatment strategies to provide better care for diabetic patients. However, the levels of need and demand for the use of technological advances have not been investigated in diabetic patients. We proposed and developed an individualized, ubiquitous (U)-healthcare service using advanced information technology for more effective glucose control. Prior to our service initiation, we surveyed patient needs and other pertinent information. METHODS: During August 2009, we conducted a 34-item questionnaire survey among patients with diabetes who were older than 40 years in two certain hospitals in Korea. RESULTS: The mean age of the 228 participants was 61.2±9 years, and males made up 49.1% of the sample. Seventy-one percent replied that they wanted individualized healthcare service, and they also wanted their health information to be delivered through mobile devices such as a cellular phone or a personal digital assistant (40.4%). Most patients had never heard of U-healthcare services (81.1%); however, after explaining the concept, 71.1% of participants responded that they would use the service if it was provided. Despite their willingness, participants were concerned about technical difficulty in using the service (26.3%) as well as the cost of the service (29.8%). CONCLUSION: The current study suggests that more than 70% of diabetic patients are interested in using U-healthcare services. To encourage widespread use, the application program or device of U-healthcare services should be simple, easy to use and affordable while also including a policy for the protection of private information.

Improved glycemic control without hypoglycemia in elderly diabetic patients using the ubiquitous healthcare service, a new medical information system.

OBJECTIVE: To improve quality and efficiency of care for elderly patients with type 2 diabetes, we introduced elderly-friendly strategies to the clinical decision support system (CDSS)-based ubiquitous healthcare (u-healthcare) service, which is an individualized health management system using advanced medical information technology. RESEARCH DESIGN AND METHODS: We conducted a 6-month randomized, controlled clinical trial involving 144 patients aged >60 years. Participants were randomly assigned to receive routine care (control, n = 48), to the self-monitored blood glucose (SMBG, n = 47) group, or to the u-healthcare group (n = 49). The primary end point was the proportion of patients achieving A1C <7% without hypoglycemia at 6 months. U-healthcare system refers to an individualized medical service in which medical instructions are given through the patient's mobile phone. Patients receive a glucometer with a public switched telephone network-connected cradle that automatically transfers test results to a hospital-based server. Once the data are transferred to the server, an automated system, the CDSS rule engine, generates and sends patient-specific messages by mobile phone. RESULTS: After 6 months of follow-up, the mean A1C level was significantly decreased from 7.8 ± 1.3% to 7.4 ± 1.0% (P < 0.001) in the u-healthcare group and from 7.9 ± 1.0% to 7.7 ± 1.0% (P = 0.020) in the SMBG group, compared with 7.9 ± 0.8% to 7.8 ± 1.0% (P = 0.274) in the control group. The proportion of patients with A1C <7% without hypoglycemia was 30.6% in the u-healthcare group, 23.4% in the SMBG group (23.4%), and 14.0% in the control group (P < 0.05). CONCLUSIONS: The CDSS-based u-healthcare service achieved better glycemic control with less hypoglycemia than SMBG and routine care and may provide effective and safe diabetes management in the elderly diabetic patients.