Esko Alasaarela

Wireless sensor and data transmission needs and technologies for patient monitoring in the operating room and intensive care unit

In the intensive care unit, or during anesthesia, patients are attached to monitors by cables. These cables obstruct nursing staff and hinder the patients from moving freely in the hospital. However, rapidly developing wireless technologies are expected to solve these problems. To this end, this study revealed problem areas in current patient monitoring and established the most important medical parameters to monitor. In addition, usable wireless techniques for short-range data transmission were explored and currently employed wireless applications in the hospital environment were studied. The most important parameters measured of the patient include blood pressures, electrocardiography, respiration rate, heart rate and temperature. Currently used wireless techniques in hospitals are based on the WMTS and WLAN standards. There are no viable solutions for short-range data transmission from patient sensors to patient monitors, but potentially usable techniques in the future are based on the WPAN standards. These techniques include Bluetooth, ZigBee and UWB. Other suitable techniques might be based on capacitive or inductive coupling. The establishing of wireless techniques depends on ensuring the reliability of data transmission, eliminating disturbance by other wireless devices, ensuring patient data security and patient safety, and lowering the power consumption and price

Measurement of respiratory rate with high-resolution accelerometer and emfit pressure sensor

Respiratory rate is an essential parameter in the clinical monitoring of hospital patients. It can be measured in various ways, such as by recording chest movements, breathing flow or heart rate variations. Current sensor technology allows the development of new kinds of convenient and portable respiratory rate recorders, including smart shirts, which enable more efficient healthcare processes in hospitals. This study carried out respiratory rate measurements using a sensor belt with a high-resolution accelerometer (capacitive MEMS) and an EMFit (electret film) pressure sensor. Results obtained from tests on 10 subjects showed that both sensors are feasible for respiratory rate measurement; the reliability of the MEMS was 90%, while that of the EMFit was 90- 100%. In addition, the results showed that the location of the sensor module on the chest is important.

A two-threshold fall detection algorithm for reducing false alarms

Wireless health monitoring can be used in health care for the aged to support independent living, either at home or in sheltered housing, for as long as possible. The most important single monitoring need with respect to security and well-being of the elderly is fall detection. In this paper, a two-threshold MATLAB-algorithm for fall detection is described. The algorithm uses mainly tri-axial accelerometer and tri-axial gyroscope data measured from the waist to distinguish between fall, possible fall, and activity of daily living (ADL). The decision between fall and possible fall is done by the posture information from the waist- and ankle-worn devices ten seconds after the fall impact. By categorizing falls into these two sub-categories, an alarm is generated only in serious falls, thus leading to low false alarm rate. The impact itself is detected as the total sum vector magnitudes of both the acceleration and angular velocity exceeds their fixed thresholds. With this method, the sensitivity of the algorithm is 95.6% with the set of 68 recorded fall events. Specificity is 99.6% with the set of 231 measured ADL movements. It is further shown that the use of two thresholds gives better results than just one threshold.

Ultrasound holographic B-scan imaging

An ultrasound holographic B-scan (UHB) imaging apparatus comprising a minicomputer system, a data acquisition unit, and a special 64-element UHB transducer has been developed. Simulation studies and real experiments with a tissue-equivalent phantom show that lateral and longitudinal resolution (-6 dB) of about 1 mm was achieved in the entire image. Furthermore, results from clinical evaluation, including diagnostic and neurosurgical imaging, suggest that the UHB imaging method is operational and has some special advantages in patient diagnosis. Theoretically, the addition of phase information to the ultrasound images can result in enhanced tissue characterization, which is extremely important in tumor diagnosis and treatment.<<ETX>>

Mutual authentication in wireless body sensor networks (WBSN) based on Physical Unclonable Function (PUF)

Wireless sensor networks are capable of deploying large, self-organized and adaptable sets of sensors for military, environmental, healthcare, remote monitoring and many other applications. Unfortunately, the simplicity and low-cost nature of these sensors make it easy for attackers to clone the authentication protocol of compromised nodes in the network. Due to unprotected nature of the wireless sensor networks, an adversary can capture messages and compromise the safety of the sensor nodes, make replicas of the authentication codes and then launch a variety of attacks with these clones. In this paper, we propose a new mutual authentication scheme for the wireless body sensor networks which is based on a Physical Unclonable Function (PUF). To identify between the sink and nodes we use a pair of challenge-response values, which are generated by the PUF in each sensor node. Also, each node needs to complete the hashed and MAC operations in the entire verification process. Analysis indicates that the scheme is efficient and robust against different attacks, such as clone attacks, replay attack, etc.

Secure key management scheme based on ECC algorithm for patient's medical information in healthcare system

Recent advances in Wireless Sensor Networks have given rise to many application areas in healthcare such as the new field of Wireless Body Area Networks. The health status of humans can be tracked and monitored using wearable and non-wearable sensor devices. Security in WBAN is very important to guarantee and protect the patients personal sensitive data and establishing secure communications between BAN sensors and external users is key to addressing prevalent security and privacy concerns. In this paper, we propose secure and efficient key management scheme based on ECC algorithm to protect patients medical information in healthcare system. Our scheme divided into three phases as setup, registration, verification and key exchange. And we use the identification code which is the SIM card number on a patients smart phone with the private key generated by the legal use instead of the third party. Also to prevent the replay attack, we use counter number at every process of authenticated message exchange to resist.

Frequency domain compensation for inhomogeneous layers in ultrasound holography

A frequency-domain compensation method is presented that is based on the ultrasound holography B-scan (UHB) imaging principle. In an acoustic imaging system, the wavefront-angle-dependent distortions caused by any kind of known inhomogeneous reason can be compensated by this method. It is applied here in the frequency domain using the so-called rear-ranging operation for the longitudinal distortion and the multiplication of phase factors for the lateral distortion. The method is especially suitable for compensating different velocity layers in acoustic imaging systems. The results of both computer simulations and water-tank experiments are promising.<<ETX>>

An ECG Analysis on Sensor Node for Reducing Traffic Overload in u-Healthcare with Wireless Sensor Network

A new approach for electrocardiogram (ECG) signal monitoring and analysis for the homecare of elderly person or patients is designed and implemented. Developed platform for real-time analysis of ECG signals on sensor node can be used as an advanced diagnosis and alarming system. Sensor node does not need to transmit ECG data all time in wireless sensor network and to server. Firstly sensor node can detect abnormality in ECG then transfer abnormal ECG data in the network to server for further analysis. This system can be used to reduce data packet overload and to save power consumption in wireless sensor network. It can also increase the server performance by reducing load. The ECG features are used to detect life-threatening arrhythmias with an emphasis of analyzing QRS complex in ECG signals at a sensor node. Based on abnormal ECG activity due to R-R interval and QRS width, the sensor node can transfer ECG data to the server for extended and cautious ECG analysis and disease classification. Needed information of abnormal ECG of a patient the server can then be transferred to the doctors personal digital assistant (PDA) for further diagnostics.

Drivers and Challenges of Wireless Solutions in Future Healthcare

What do IT-oriented healthcare professionals believe to be the most attractive and credible wireless applications in healthcare? What do they think about the challenges? These questions were presented to 70 randomly selected participants at the HIMSS08 conference in February 2008 at Orlando, Florida, USA. The questions were formulated in a one-page query form and the data was uploaded into the ZEF-analysis tool (zefsolutions.com/en). Results show that on average the most attractive and credible application is wireless alarming and calling help. The second and third are mobile access to patient health records and vital signs monitoring. The results also show that process change challenges are remarkably more difficult than technical challenges. The process change from the doctors’ point of view is particularly severe. Among technical challenges usability of the mobile user interface is seen the most difficult. Security of patient data is not considered to be among the most severe challenges.

Physical violence detection for preventing school bullying

School bullying is a serious problem among teenagers, causing depression, dropping out of school, or even suicide. It is thus important to develop antibullying methods. This paper proposes a physical bullying detection method based on activity recognition. The architecture of the physical violence detection system is described, and a Fuzzy Multithreshold classifier is developed to detect physical bullying behaviour, including pushing, hitting, and shaking. Importantly, the application has the capability of distinguishing these types of behaviour from such everyday activities as running, walking, falling, or doing push-ups. To accomplish this, the method uses acceleration and gyro signals. Experimental data were gathered by role playing school bullying scenarios and by doing daily-life activities. The simulations achieved an average classification accuracy of 92%, which is a promising result for smartphone-based detection of physical bullying.