Mobile forensic triage for damaged phones using M_Triage

Mobile forensics triage is a useful technique in a digital forensics investigation for recovering lost or purposely deleted and hidden files from digital storage. It is particularly useful, especially when solving a very sensitive crime, for example, kidnapping, in a timely manner. However, the existing mobile forensics triage tools do not consider performing a triage examination on damaged mobile phones. This research addressed the issues of performing triage examination on damaged Android mobile phones and reduction of false positive result generated by the current mobile forensics triage tools. Furthermore, the research addressed the issues of ignoring possible evidence residing in a bad block memory location. In this research a new forensics triage tool called M_Triage was introduced by extending Decode’s framework to handle data retrieval challenges on damaged Android mobile phones. The tool was designed to obtain evidence quickly and accurately (i.e. valid address book, call logs, SMS, images, and, videos, etc.) on Android damaged mobile phones. The tool was developed using C#, while back end engines was done using C programming and tested using five data sets. Based on the computational time processing comparison with Dec0de, Lifter, XRY and Xaver, the result showed that there was 75% improvement over Dec0de, 36% over Lifter, 28% over XRY and finally 71% over Xaver. Again, based on the experiment done on five data sets, M_Triage was capable of carving valid address book, call logs, SMS, images and videos as compared to Dec0de, Lifter, XRY and Xaver. With the average improvement of 90% over DEC0DE, 30% over Lifter, 40% over XRY and lastly 61% over Xaver. This shows that M_Triage is a better tool to be used because it saves time, carve more relevant files and less false positive result are achieved with the tool

Using Type-2 Fuzzy Models to Detect Fall Incidents and Abnormal Gaits Among Elderly

— June 2012, 11% of the overall population in Taiwan was over the age of 65. This ratio is higher than the average figure for the United Nations (8%) . Critical issues concerning elderly in healthcare include fall detection, loneliness prevention and retard of obliviousness. In this study we design type-2 fuzzy models that utilize smart phone tri-axial accelerometer signals to detect fall incidents and identify abnormal gaits among elderly. Once a fall incident is detected an alarm is sent to notify the medical staff for taking any necessary treatment. When the proposed system is used as a pedometer, all the tri-axial accelerometer signals are used to identify the gaits during walking. Based on the proposed type-2 fuzzy models, the walking gaits can be identified as normal, left-tilted, and right-tilted. Experimental results from type-2 fuzzy models reveal that the accuracy rates in identifying normal walking and fall over are 92.3% and 100%, respectively, exceeding what are obtained using type-1 fuzzy models

Mobile forensic triage for damaged phones using M_Triage

Mobile forensics triage is a useful technique in a digital forensics investigation for recovering lost or purposely deleted and hidden files from digital storage. It is particularly useful, especially when solving a very sensitive crime, for example, kidnapping, in a timely manner. However, the existing mobile forensics triage tools do not consider performing a triage examination on damaged mobile phones. This research addressed the issues of performing triage examination on damaged Android mobile phones and reduction of false positive result generated by the current mobile forensics triage tools. Furthermore, the research addressed the issues of ignoring possible evidence residing in a bad block memory location. In this research a new forensics triage tool called M_Triage was introduced by extending Decode’s framework to handle data retrieval challenges on damaged Android mobile phones. The tool was designed to obtain evidence quickly and accurately (i.e. valid address book, call logs, SMS, images, and, videos, etc.) on Android damaged mobile phones. The tool was developed using C#, while back end engines was done using C programming and tested using five data sets. Based on the computational time processing comparison with Dec0de, Lifter, XRY and Xaver, the result showed that there was 75% improvement over Dec0de, 36% over Lifter, 28% over XRY and finally 71% over Xaver. Again, based on the experiment done on five data sets, M_Triage was capable of carving valid address book, call logs, SMS, images and videos as compared to Dec0de, Lifter, XRY and Xaver. With the average improvement of 90% over DEC0DE, 30% over Lifter, 40% over XRY and lastly 61% over Xaver. This shows that M_Triage is a better tool to be used because it saves time, carve more relevant files and less false positive result are achieved with the tool

Development of a Step Counting Algorithm Using the Ambulatory Tibia Load Analysis System for Tibia Fracture Patients

Introduction: Ambulation can be used to monitor the healing of lower extremity fractures. However, the ambulatory behavior of tibia fracture patients remains unknown due to an inability to continuously quantify ambulation outside of the clinic. The goal of this study was to design and validate an algorithm to assess ambulation in tibia fracture patients using the ambulatory tibial load analysis system during recovery, outside of the clinic. Methods Data were collected from a cyclic tester, 14 healthy volunteers performing a 2-min walk test on the treadmill, and 10 tibia fracture patients who wore the ambulatory tibial load analysis system during recovery. Results The algorithm accurately detected 2000/2000 steps from simulated ambulatory data. (see full text for full abstract

A review of activity trackers for senior citizens: research perspectives, commercial landscape and the role of the insurance industry

The objective assessment of physical activity levels through wearable inertial-based motion detectors for the automatic, continuous and long-term monitoring of people in free-living environments is a well-known research area in the literature. However, their application to older adults can present particular constraints. This paper reviews the adoption of wearable devices in senior citizens by describing various researches for monitoring physical activity indicators, such as energy expenditure, posture transitions, activity classification, fall detection and prediction, gait and balance analysis, also by adopting consumer-grade fitness trackers with the associated limitations regarding acceptability. This review also describes and compares existing commercial products encompassing activity trackers tailored for older adults, thus providing a comprehensive outlook of the status of commercially available motion tracking systems. Finally, the impact of wearable devices on life and health insurance companies, with a description of the potential benefits for the industry and the wearables market, was analyzed as an example of the potential emerging market drivers for such technology in the future

Southwest Research Institute assistance to NASA in biomedical areas of the technology

Significant applications of aerospace technology were achieved. These applications include: a miniaturized, noninvasive system to telemeter electrocardiographic signals of heart transplant patients during their recuperative period as graded situations are introduced; and economical vital signs monitor for use in nursing homes and rehabilitation hospitals to indicate the onset of respiratory arrest; an implantable telemetry system to indicate the onset of the rejection phenomenon in animals undergoing cardiac transplants; an exceptionally accurate current proportional temperature controller for pollution studies; an automatic, atraumatic blood pressure measurement device; materials for protecting burned areas in contact with joint bender splints; a detector to signal the passage of animals by a given point during ecology studies; and special cushioning for use with below-knee amputees to protect the integrity of the skin at the stump/prosthesis interface