[Show abstract][Hide abstract] ABSTRACT: Multiple toilet grab-bar configurations are required by people with a diverse spectrum of disability. The study purpose was to determine
toilet grab-bar preference of healthy seniors, seniors with a hip replacement, and seniors post-stroke, and to determine the effect of each
configuration on centre of pressure (COP) displacement during toilet transfers. METHODS: 14 healthy seniors, 7 ambulatory seniors with
a hip replacement, and 8 ambulatory seniors post-stroke participated in the study. Toilet transfers were performed with no bars (NB),
commode (C), two vertical bars (2VB), one vertical bar (1VB), a horizontal bar (H), two swing-away bars (S) and a diagonal bar (D).
COP was measured using pressure sensitive floor mats. Participants rated the safety, ease of use, helpfulness, comfort and preference for
instalment. RESULTS: 2VB was most preferred and had the smallest COP deviation. Least preferred was H and NB. C caused largest
COP displacement but had favourable ratings. DISCUSSION: The preference and safety of the 2VB should be considered in the design of
accessible toilets and in accessibility construction guidelines. However these results need to be verified in non-ambulatory populations. C is
frequently prescribed, but generates large COP deviation, suggesting it may present an increased risk of falls.
Full-text · Article · Oct 2015 · Assistive technology: the official journal of RESNA
[Show abstract][Hide abstract] ABSTRACT: Automated assessment of older adult health is needed due to an impending demographic shift. Mobility is considered an indicator of health and is more tangible than some other health measures. Currently, many papers aim to examine a discrete movement in detail, but none describe one system of algorithms aiming to automatically identify discrete and continuous patient positions and transitions. This paper aims to develop such a system of algorithms. Discrete and continuous data were generated by 32 subjects performing a series of position-transition movements, captured by fiber-optic pressure sensor mats. Algorithm set 1 part 1 aimed to identify and distinguish between three positional states by extracting seven occupancy and dispersion features, then using 1-D and 2-D support vector machine (SVM) and linear classifiers to classify the data. Set 1 part 2 aimed to identify and distinguish between state transitions by calculating percentage pressure difference on a per sensor and large area basis, then monitoring these signals for pressure relief. The second set aimed to examine all movements by extracting six geometric features from center of pressure signals, then using 1-D and 2-D SVM and linear classifiers to classify two subtly different transitions. All methods resulted in at least a 98% identification accuracy, and some methods were able to shed light on the subtleties of transitions. The results suggest that, with more development, the presented algorithmic methods could be implemented in hospital settings to assist with identification and assessment of elderly patient mobility.
No preview · Article · Aug 2015 · IEEE Transactions on Instrumentation and Measurement
[Show abstract][Hide abstract] ABSTRACT: The accelerometer has become one of the most popular sensors in recent years due to its low cost and the widespread availability of smart phones that now contain three axis accelerometers. This paper proposes an adaptive drift calibration technique for accelerometer signals, correcting higher sampling rate accelerometers using lower sampling rate velocity and position measurements. Specifically, this study made use of 40Hz sampled accelerometer signals captured by smart phones, and corrected them using two different 1Hz sampled velocity reference signals: a vehicle speed sensor and velocity from a Global Positioning System position sensor. The paper compares the performance of two error correction algorithms based on step and ramp shaped error correction delta functions. The ramp function was found to be susceptible to oscillation caused by high frequency noise, while the step function remains stable. The paper also shows that the GPS velocity signal has better performance over the dashboard vehicle velocity signal due to the higher frequency noise within the direct velocity signal.
No preview · Article · Jul 2015 · Conference Record - IEEE Instrumentation and Measurement Technology Conference
[Show abstract][Hide abstract] ABSTRACT: This paper demonstrates the validity of vehicle acceleration/deceleration signals derived from 1Hz sampled GPS position and OBDII velocity sensors through comparison to 40Hz sampled accelerometer measurements. Measurement of driver acceleration and deceleration is important because it is a key measure of driving habits. Ideally, these measurements should not require the cost and complexity of installing dedicated accelerometers for long term studies when alternatives are available. The OBDII interface is built-in and GPS sensors can be easily deployed and both are shown to allow derivation of alternative acceleration signals. The results show a maximum average correlation of 0.810 between the GPS and the accelerometers and 0.808 between the OBDII and the accelerometer. This paper analyzes the effects of noise on each of the derivative difference equations and shows that the Central 2-point formula provides the best noise performance whereas the Central 4-point formula (correlation 0.801) would be expected to provide the best performance in a noise free signal. Forward/Backward 3-point are predicted to have similar performance to Central 2-point in noise free signals but are shown to have poor performance (correlation of 0.667 and 0.687 respectively) in the presence of noise.
[Show abstract][Hide abstract] ABSTRACT: This paper presents the analysis of all driving by a single (female) older diver over a one year period from the Candrive project. Data analytics techniques have been applied to this unique big data set that includes 1 Hz sampled Global Positioning System (GPS) and Geographic Information System (GIS) data and includes the analysis of 1562 trips covering 13,425 km. The driver is known to have stable general, cognitive and physical health through clinical testing at the start and end of the 1 year period. The paper specifically explores the deceleration habits of the driver by locating all deceleration events over the period with a net velocity drop of 4km/hr or more resulting in 24,794 events being identified. The paper finds that the mean and minimum deceleration values for the events, both have two phases where the deceleration values increase with the size of the velocity drop (-0.252 and-0.0593 hr·m/km·s2 respectively) until the drop exceeds 27.5km/hr and then the second phase has a much lower slope (-0.027 and-0.0053 hr·m/km·s2 respectively). Subsets of the deceleration events such as posted speed limit on road and decelerations ending with a stopped vehicle exhibit the same two phase relationship. The two phases and their transition are attributes of the deceleration habits for the driver that may potentially be used to distinguish between drivers of a vehicle.
[Show abstract][Hide abstract] ABSTRACT: Thermal imaging is of value to medical professionals because of its low risk and non-invasive properties. While thermal imaging has been explored in the area of pressure ulcers, many relevant papers address existing pressure ulcers and few address the prevention of pressure ulcers. This paper aims to examine the potential of thermal imaging in the prevention of pressure ulcers by extracting temperature-based and region-based measurements from thermal images and quantifying thermal patterns. A subject was asked to press on a pressure sensor mat at two specified intensities, and a series of thermal images were taken before and after to track thermal behaviour. These images were subjected to standard image processing techniques before temperature specific contour and area measurements were extracted as well as region specific intensity and weighted centroid measurements. Results indicated that the contour and area measurements were able to capture the temperature pattern of the whole hand, while the intensity measurements were able to indicate region specific thermal patterns. These results suggest that the extraction of measurements from a series of thermal images can capture and quantify visually identifiable thermal patterns of the hand over time. These findings will be expanded upon in future work by further examining different measurements, sharper images, different equipment and the involvement of elderly patients. While future collection of patient data is expected to yield different thermal patterns, this paper has demonstrated recognition and quantification of a pattern, regardless of the pattern itself.
[Show abstract][Hide abstract] ABSTRACT: Measurement of a single source by multiple sensors can produce signals that are synchronous but reversed: one signal rises while the other falls. Combining the signals can produce a better signal quality than a single sensor, but detection and correction of the reversals is crucial to avoid destructive interference. Conventional time delay estimation (TDE) methods are good detection tools but may be hampered by conditions such as drift, low signal to noise ratios, and burst interference. Furthermore, these methods are designed for stationary periodic signals, and are susceptible to nonstationary behavior present in the physical world. A method of detection based on the signal slope and a fused reference is presented. Simulations for signals with varying levels of interference were analyzed. A tradeoff between immunity to drift and immunity to noise was controllable by a window length parameter. The proposed method was robust to the simulated interference, withstanding more than 10-dB higher noise and drift than conventional TDE methods. A real-world experiment to extract breathing from a bed-based pressure sensor array was also run. Mean correlations of extracted respiration to gold standard respiration curves were 0.863, achieving a 32% performance improvement over not detecting and correcting the reversals, and a 7% improvement over the conventional detection methods.
No preview · Article · Dec 2014 · IEEE Transactions on Instrumentation and Measurement
[Show abstract][Hide abstract] ABSTRACT: This paper uses data analytics to provide a method for the measurement of a key driving task, turn signal usage as a measure of an automatic over-learned cognitive function drivers. The paper augments previously reported more complex executive function cognition measures by proposing an algorithm that analyzes dashboard video to detect turn indicator use with 100% accuracy without any false positives. The paper proposes two algorithms that determine the actual turns made on a trip. The first through analysis of GPS location traces for the vehicle, locating 73% of the turns made with a very low false positive rate of 3%. A second algorithm uses GIS tools to retroactively create turn by turn directions. Fusion of GIS and GPS information raises performance to 77%. The paper presents the algorithm required to measure signal use for actual turns by realigning the 0.2Hz GPS data, 30fps video and GIS turn events. The result is a measure that can be tracked over time and changes in the driver's performance can result in alerts to the driver, caregivers or clinicians as indication of cognitive change. A lack of decline can also be shared as reassurance.
[Show abstract][Hide abstract] ABSTRACT: This paper presents a new approach for analyzing center of pressure (COP) progression using pressure data collected from a pressure-sensitive array placed under the bed mattress. Pressure data were collected from a young female participant who was healthy and an older 78 year old female participant who had a history of falls. Information relevant to movement direction, time, path trajectory, magnitude and frequency was presented in three dimensional plots and color differentiated displays. When tested on data collected from an older participant who experienced a fall, this method of analyzing COP was able to illustrate distinct differences in bed exit patterns used pre and post fall episode. This analysis approach shows the potential to detect changes in bed exit patterns indicative of a critical health event. Future applications include home monitoring to assist with early intervention in the event of bed mobility decline.
[Show abstract][Hide abstract] ABSTRACT: Palliative care needs are growing with the aging population. Ambient sensors offer patients comfortable and discreet point-of-care monitoring. In this study, two palliative care participants were monitored in a sensorized bed. Motion monitoring by a two-tier gross and fine movement detector provided accurate detection and classification of movement, compared to annotations by an observer. However, ascribing the motion to the patient rather than caregivers or visitors would require supplemental sensors. Motion was indicative of pain, with 13% of time spent moving while in pain versus 3% while not noted as in pain.
[Show abstract][Hide abstract] ABSTRACT: The arterial blood pressure (ABP) is one of the most important physiological parameters for health monitoring. Most of the blood measurement devices in the market determine the ABP through the inflation and the deflation of a cuff controlled by a bladder. This method is very uncomfortable for most of the users and may even cause anxiety, which in turn can affect the blood pressure (BP) (white coat syndrome). This paper investigates a cuffless nonintrusive approach to estimate the BP. The main idea is to measure the pulse transit time (PTT), i.e., the delay between the R-peak of the electrocardiogram (ECG) signal and the following peak of the finger photoplethysmograph (PPG) signal. The main problem of this approach is that when the dicrotic notch of the PPG signal is unobservable, the position and the amplitude of the main peak of the PPG signal will be changed. As a result, the correlation between the BP and the PTT can be affected. To overcome this problem, three types of secondary peak detection methods are designed to reveal the secondary peak from the original PPG signal. Actual ECG, PPG, and the BP measurements extracted from the Multiparameter Intelligent Monitoring in Intensive Care II database that contains clinical signal data reflecting real measurements are used. The results verify that the proposed detection methods improve the correlation relationship between the BP and the PTT, and demonstrate that the adjusted PTT can be used as an indicator of the ABP by removing the dicrotic notch impact on the PPG signal.
No preview · Article · Jun 2014 · IEEE Transactions on Instrumentation and Measurement
[Show abstract][Hide abstract] ABSTRACT: Proliferation of wearable devices and the “quantified self” behavior creates massive amounts of data acquired from physiological sensors. Unfortunately this vast amount of data is to date largely untapped for clinical purposes because of low data reliability caused by issues such as contact noise and motion artifacts. One important physiological signal is ECG and one of its important features is the heart rate, obtained from the QRS complex of the ECG signal or beat detection algorithms. This feature is important in characterizing Heart Rate Variability (HRV) and detecting various pathologies such as arrhythmia, chronic heart failure, or sleep apnea. Many such algorithms simply discard data segments which are deemed “unreliable” due to errors in QRS detection. This paper analyzes the impact of changing the noise level and noise duration on the percentage of data segments that are discarded. The paper proposes an approach to improve the usability of ECG data corrupted by noise by analyzing the impact of noise on features of interest and adapting relevant system parameters accordingly. The proposed approach can be used with any classifier operating on short-term HRV features.
[Show abstract][Hide abstract] ABSTRACT: This paper explores analysis techniques to distinguish between differing drivers of a vehicle. This is a new research challenge as there are numerous examples where there is a need to measure and monitor the ability of a particular driver in shared vehicles. In older adults, cognitive decline or illness can affect their driving ability, younger drivers that have restricted licenses may need monitoring for compliance, and professional drivers are subject to hours of work restrictions. The use of GPS and engine computer data loggers has simplified the recording of detailed driving information, but the identification of the driver remains a challenge as techniques such as RFID tags and user logs all have errors and omissions. The Candrive project is capturing extensive records for 256 vehicles in Ottawa over a 5 year period where GPS and OBDII logs are captured. This paper presents preliminary analysis of 100 trips for 4 different drivers and shows the potential for time of day, road choice, velocity and acceleration data analytics analysis to provide attributes to distinguish between drivers of a vehicle that will enable the future creation of a driving signature.
[Show abstract][Hide abstract] ABSTRACT: Recent advances in sensor technology and mobile computing are now enabling practical non-intrusive approaches to measure vital signs and other biological signals. Furthermore, most smart phones are now equipped with high resolution cameras and powerful processors that can reliably measure these signals. One of the signals of interest is the pulse transit time that is often correlated with changes in the blood pressure and stress level. Conventional techniques for measuring pulse transit time are based on measuring the electrocardiogram (ECG) signal using leads attached to the chest and measuring the plethysmograph (PPG) signal from a finger. This paper proposes a novel approach to measure pulse transit time non-intrusively using the Eulerian video magnification framework, particularly Eulerian color magnification. The proposed approach uses a video camera to capture a standard video sequence of the subject. After applying spatial decomposition and temporal filtering to the frames, the filtered signal is then amplified to reveal the subtle changing, like the color changing on different spots caused by the blood pulse. Two spots, the wrist and the neck, were selected to measure the pulse transit time. To verify the performance and practicability of the proposed system, the measured pulse transit time were compared with the time difference detected using a conventional technique based on two Pulse Sensors and the Arduino board. Ten subjects were studied under three status, climbing stairs, five minutes rest after climbing stairs, and twenty minutes rest after climbing stairs. The experimental results show that the pulse transit time measured by the Eulerian video magnification framework is highly correlated with the pulse transit time detected by pulse sensors, demonstrating that the proposed approach has the potential to be used for health-care monitoring.
[Show abstract][Hide abstract] ABSTRACT: The sit-to-stand transfer has been examined in depth using many different methods. Pressure mats and or force plates have been used to partition the transfer into phases. These phases help to identify the beginning and end of the transfer and describe the movement performance, therefore characterizing the transition. The methods of phase breakdown, however, vary depending on the source. In this paper, the objective was to distinguish between a vigorous sit to stand transfer and a slower, less stable sit to stand transfer using a different approach. Ten subjects performed two sit-to-stand transfers each on a hospital mattress, while pressure sensors underneath the mattress gathered movement data. The center of mass was calculated and three features were extracted, then evaluated by a classifier to determine if the features could distinguish between the two movements. Examination of the results determined that two of the three features yielded total accuracy, despite inconsistencies in subject performance. These results suggest that the center of pressure can be used to distinguish between slow, unstable sit-to-stand transfers and vigorous ones. Future work will include the examination of center of pressure in the measurement of balance, as well as the overall assessment of sit-to-stand performance.
[Show abstract][Hide abstract] ABSTRACT: Remote Patient Monitoring (RPM) systems will play an important role in the future of healthcare. They will be used to monitor chronic conditions, but may also be employed to detect acute medical conditions and generate alarms in real-time. This real-time responsiveness is a critical design criterion for acute condition detection. The data rate of each sensor represents a hard real-time threshold; if an RPM system cannot process incoming data as quickly as it arrives, its perception of a patient's health status will gradually begin to lag behind that patient's actual status. One effective way to address this issue is to select an operating system (OS) that can effectively manage data analysis for the highest priority tasks under all possible CPU load conditions. This paper evaluates the performance of a real-time operating system (RTOS)-based multi-sensor RPM system. The real-time system performance is measured against a hard realtime processing threshold for five simulated sensor inputs with varying priority levels. The results demonstrate that preemptive scheduling, employed by the RTOS, allows an RPM system under heavy processing load to consistently meet the hard real-time threshold requirements for acute condition detection.
[Show abstract][Hide abstract] ABSTRACT: This paper presents the design and validation of two computer games for the monitoring and measurement of cognitive change. Computer games that claim to improve cognitive ability are focused on healthy players while the testing of these games has been limited to healthy adults and has typically not included older adults with Mild Cognitive Impairment (MCI). The two games presented in this paper have specific features to aid and monitor cognitively impaired users including a hint system so that players do not become frustrated with the games. Cognitive performance is measured through a game play log in the Carleton Word Search Game (CWG) and Carleton Sudoku Game (CSG) that has been designed into the games. The paper presents how the measures indicate user performance across the various aspects of game play such as search, logic and general motor skills. The paper presents the results of initial validation tests using cognitive distraction to simulate cognitive impairment.
[Show abstract][Hide abstract] ABSTRACT: The growing need to gain efficiencies within a home care setting has prompted home care practitioners to focus on health informatics to address the needs of an aging clientele. The remote and heterogeneous nature of the home care environment necessitates the use of non-intrusive client monitoring and a portable, point-of-care graphical user interface. Using a grounded theory approach, this article examines the simulated use of a graphical user interface by practitioners in a home care setting to explore the salient features of monitoring the activity of home care clients. The results demonstrate the need for simple, interactive displays that can provide large amounts of geographical and temporal data relating to patient activity. Additional emerging themes from interviews indicate that home care professionals would use a graphical user interface of this type for patient education and goal setting as well as to assist in the decision-making process of home care practitioners.
No preview · Article · May 2014 · Health Informatics Journal
[Show abstract][Hide abstract] ABSTRACT: Acoustic echo cancellation is one of the most severe requirements in hands-free telephone and teleconference communication. This paper proposes an Empirical Mode Decomposition (EMD)-based sub-band adaptive filtering structure, which applies the EMD-based algorithm dealing with the far-end speech signal and the microphone output to obtain two sets of intrinsic mode functions (IMFs). In addition, each IMF set is separated into different bands based on the power spectral density (PSD) of every IMF. Experiment signals were collected from a medium-size office room and simulations were taken under different conditions by three types of EMD-based algorithms. Results show that the proposed structure is able to model the transfer function of the unknown environment and track the change of the room much faster than the normalized adaptive filtering structure. The ensemble EMD (EEMD) algorithm and the noise-modulated EMD (NEMD) are proved to have better performance than the EMD algorithm in terms of echo return loss enhancement.
No preview · Article · Mar 2014 · International Journal of Speech Technology
[Show abstract][Hide abstract] ABSTRACT: Background: Transfer training is commonly provided as part of rehabilitation efforts to improve the independence of geriatric patients. Although a number of functional clinical measures include components involving sit-to-stand, none focus solely on this ability which is fundamental to independence.
Objective: To determine whether pressure-sensitive mat technology can measure changes in sit-to-stand transfer times among Day Hospital patients over the course of treatment.
Methods: An S4 pressure-sensitive mat was placed under a bed mattress and connected to a computer. Participants were asked to rise from the bed at 3 points in time during the course of treatment at a Day Hospital (i.e. admission, midpoint, discharge). Computerized algorithms were used to determine sit-to-stand transfer times based on pressure-sensitive mat data. Functional performance measures (Berg Balance Scale, 6 Minute Walk Test and Timed Up & Go) were also collected at three points in time.
Results: Twenty-eight patients, mean age 81 years, agreed to participate. Mean sit-to-stand times were 1.69 seconds at admission, 1.58 seconds at midpoint and 1.39 seconds at discharge. All functional performance measure means improved -Timed Up & Go by 8.1 seconds, Berg Balance Scale by 4.4 points and 6 Minute Walk Test by 79 meters.
Conclusion: The pressure-sensitive mat detected a trend of improving sit-to-stand times which corresponded with clinical improvements. Further research is required to confirm correlations between mat and clinical data. The ability to monitor changes with pressure-sensitive mat technology has implications for being able to detect declines in mobility remotely following discharge from hospital.