Chih-Yen Chiang

A Reliable Transmission Protocol for ZigBee-Based Wireless Patient Monitoring

Patient monitoring systems are gaining their importance as the fast-growing global elderly population increases demands for caretaking. These systems use wireless technologies to transmit vital signs for medical evaluation. In a multihop ZigBee network, the existing systems usually use broadcast or multicast schemes to increase the reliability of signals transmission; however, both the schemes lead to significantly higher network traffic and end-to-end transmission delay. In this paper, we present a reliable transmission protocol based on anycast routing for wireless patient monitoring. Our scheme automatically selects the closest data receiver in an anycast group as a destination to reduce the transmission latency as well as the control overhead. The new protocol also shortens the latency of path recovery by initiating route recovery from the intermediate routers of the original path. On the basis of a reliable transmission scheme, we implement a ZigBee device for fall monitoring, which integrates fall detection, indoor positioning, and ECG monitoring. When the triaxial accelerometer of the device detects a fall, the current position of the patient is transmitted to an emergency center through a ZigBee network. In order to clarify the situation of the fallen patient, 4-s ECG signals are also transmitted. Our transmission scheme ensures the successful transmission of these critical messages. The experimental results show that our scheme is fast and reliable. We also demonstrate that our devices can seamlessly integrate with the next generation technology of wireless wide area network, worldwide interoperability for microwave access, to achieve real-time patient monitoring.

Development of a Fall Detecting System for the Elderly Residents

Accidental falls are common causes of serious injury and health threats in the elder population. To deliver adequate medical support, the robust and immediate falls detection is important. Since the fall detection in the elderly remains a major challenge in the public health domain, effective fall-detection will provide urgent support and dramatically reduce the cost of medical care. In this work, we propose a fall-detecting system placing an accelerometer on the head level and using an algorithm to distinguish between falls and daily activities. The experimental results have demonstrated the proposed scheme with high reliability and sensitivity on fall detection. The system is not only cost effectively but also potable. It fulfills the requirements of fall detection.

A reliable fall detection system based on wearable sensor and signal magnitude area for elderly residents

Falls are the primary cause of accidents for elderly people and often result in serious injury and health threats. It is also the main obstacle to independent living for frail and elderly people. A reliable fall detector can reduce the fear of falling and provide the user with the reassurance to maintain an independent lifestyle since the reliable and effective fall detection mechanism will provide urgent medical support and dramatically reduce the cost of medical care. In this work, we propose a fall-detecting system based on a wearable sensor and a real-time fall detection algorithm. We use a waist- mounted tri-axial accelerometer to capture movement data of the human body, and propose a fall detection method that uses the area under a signal magnitude curve to distinguish between falls and daily activities. Experimental results demonstrate the effectiveness of proposed scheme with high reliability and sensitivity on fall detection. The system is not only cost effective but also portable that fulfills the requirements of fall detection.

Abnormality detection for improving elder's daily life independent

Since the dramatic demographic change makes it inevitable that rapid aging of the population is an unprecedented phenomenon in Taiwan. A growing social problem is supporting older adults who want to live independently in their own homes. It needs a health assistance system to make them independent living up to a higher age. Recently, technological advancements have spurred various ideas and innovations to assist the elders living independently. In this paper, we proposed a homecare sensory system that uses RFID-based sensor networks to collect elders daily activities and conducts the data into Hidden Markov model (HMM) and Support Vector Machines (SVMs) to estimate whether the elders behavior is abnormal or not. Through detecting and distinguishing the abnormal behaviors of elders daily activities, the system provides assistance on elders independent living and improvement of aged quality of life.

Location-Aware Fall Detection System for Medical Care Quality Improvement

Abstract—Falls are one of the most common adverse events in hospitals and fall management remains a major challenge in the medical care quality. Falls in patients are associated with major health complications that can result in health decline and increased medical care cost. To deliver medical care in time, reliable location-aware fall detection is needed. In this paper, we propose a patient alert alarm for fall management. It is ZigBee-Based location awareness fall detection system that provides immediate position information to the caregivers as soon as the fall happened. Obviously, the integration of location awareness and fall detection technologies fulfills the requirements of delivering critical information to relative professions and improve the medical care quality.

An Intelligent RFID System for Improving Elderly Daily Life Independent in Indoor Environment

Since elderly obliviousness causes social inconvenience and psychical complaint, elders often forget daily schedules and miss their personal belongings such pillboxes or keys. Recently, technological advancements have spurred various ideas and innovations to apply on elder independent living. In this article, we proposed an intelligent RFID (Radio Frequency Identification) system to assist elder living independent and improve aged quality of life.

Data Collection and Analysis Using Wearable Sensors for Monitoring Knee Range of Motion after Total Knee Arthroplasty

Total knee arthroplasty (TKA) is the most common treatment for degenerative osteoarthritis of that articulation. However, either in rehabilitation clinics or in hospital wards, the knee range of motion (ROM) can currently only be assessed using a goniometer. In order to provide continuous and objective measurements of knee ROM, we propose the use of wearable inertial sensors to record the knee ROM during the recovery progress. Digitalized and objective data can assist the surgeons to control the recovery status and flexibly adjust rehabilitation programs during the early acute inpatient stage. The more knee flexion ROM regained during the early inpatient period, the better the long-term knee recovery will be and the sooner early discharge can be achieved. The results of this work show that the proposed wearable sensor approach can provide an alternative for continuous monitoring and objective assessment of knee ROM recovery progress for TKA patients compared to the traditional goniometer measurements.

MID-based electronic data collection and adaptive drug delivery model for improving quality of PCA services

Patient-Controlled Analgesia (PCA) is an important means of self-regulated pain relief service and has been widely used in postoperative pain management. In order to improve the defects and risks of paper-based data collection, we propose a web-based electronic data collection (EDC) system to support PCA services. The successful website design involves a clearly communicated stepwise process that specifies the development of each PCA EDC module. We performed a simple usability evaluation of the EDC system by measuring the data collection time during the visitation. The results demonstrated that web-based EDC system had better efficiency than that of traditional non-web-based EDC system. Through conveying the PCA initial settings and dosage information of the first 48-hour therapy as input variables, we proposed an adaptive drug delivery model to provide precise dosage information to deliver effective analgesia of PCA services. The adaptive drug delivery model can not only explore the relationship of analgesia drug consumption and related factors, but also further provide useful analgesia dosage reference to the anesthesiologists.

Pervasive Communications for Care Professionals in Hospitals

It has been demonstrated that effective communications among specialists is essential in the delivery of high quality of patient care. A location-enabled VoWLAN service may further bring seamless connections for medical professionals to communicate and collaborate with each other efficiently. It greatly assists the locating relative professionals in hospital urgencies and delivering critical information to specific professionals. In this article, we proposed an enhanced Hospital Patient Care Call System (EHPC2S), which converges the voice and context information for the purpose of reducing medical errors and providing better hospital quality of service.