Vilas Joshi

Sequence estimation techniques for digital subscriber loop transmission with crosstalk interference

The use of reduced-state sequence estimation techniques in a digital subscriber loop receiver is discussed. These techniques offer a potential performance improvement over conventional equalization techniques such as decision feedback equalization (DFE). Stationary and cyclostationary NEXT noise models are described. The theoretical performance obtainable from a Viterbi algorithm receiver with stationary white Gaussian noise, stationary NEXT, and cyclostationary NEXT noise models is estimated, and the reduced-state decision feedback sequence estimation and M algorithms are reviewed. It is shown that the improvement can be especially significant in the presence of cyclostationary crosstalk because of the freedom that sequence estimation receivers afford in the choice of receiver sampling phase. This advantage is evaluated for Viterbi algorithm receivers. By simulation of two practical reduced-state sequence estimation receivers, it is demonstrated that, in the presence of cyclostationary crosstalk, a substantial increase in maximum loop range (or equivalently, maximum bit rate) may be achievable compared to conventional DFE equalization. >

Using a real-time operating system for multitasking in Remote Patient Monitoring

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 patients health status will gradually begin to lag behind that patients 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.

Reduced-complexity trellis coding/decoding for high bit rate digital subscriber loop transmission

The authors describe an adaptive piecewise-linear-fit technique for closely approximating channel response, using relatively few parameters. Theoretical and simulation results for the approximation error and adaptation behavior of this technique are shown for representative channel responses. The results indicate the viability of the technique for decision-feedback equalizers used within or outside reduced state sequence estimators.<<ETX>>

Measuring sit-to-stand timing variability over time using under mattress pressure sensor technology

Getting out of bed is a fundamental activity of daily living and one that supports independent living. Under mattress pressure sensor technology represents a way to monitor changes in this basic but critical mobility task among older adults at risk of institutionalization. However, little is known about normal variations in this ability over time in the home context. This study used under mattress pressure sensors to measure and analyze the variability of sit-to-stand (STS) timing in a community-dwelling older adult. A pressure-sensitive mat was installed in the participants home and left in place to collect information over a period of nine months. A processing algorithm was developed to extract the STS phase of the first morning bed exit from which STS time could be measured. STS timing data were visualized using a histogram and analyzed for trends over the extended period using nonparametric regression and wavelet analysis. Results indicate that the analytical methods used were able to identify trends in STS timing as well as highlight deviations. The ability to collect and analyze the variability of STS timing using this pressure sensitive technology combined with the analysis methodology provides clinicians with a way to assess mobility remotely in the home setting.

Highly survivable bed pressure mat remote patient monitoring system for mHealth

The high speed mobile networks like 4G and beyond are making a ubiquitous remote patient monitoring (RPM) system using multiple sensors and wireless sensor networks a realistic possibility. The high speed wireless RPM system will be an integral part of the mobile health (mHealth) paradigm reducing cost and providing better service to the patients. While the high speed wireless RPM system will allow clinicians to monitor various chronic and acute medical conditions, the reliability of such system will depend on the network Quality of Service (QoS). The RPM system needs to be resilient to temporary reduced network QoS. This paper presents a highly survivable bed pressure mat RPM system design using an adaptive information content management methodology for the monitored sensor data. The proposed design improves the resiliency of the RPM system under adverse network conditions like congestion and/or temporary loss of connectivity. It also shows how the proposed RPM system can reduce the information rate and correspondingly reduce the data transfer rate by a factor of 5.5 and 144 to address temporary network congestion. The RPM system data rate reduction results in a lower specificity and sensitivity for the features being monitored but increases the survivability of the system from 1 second to 2.4 minutes making it highly robust.

Bed occupancy monitoring: Data processing and clinician user interface design

Unobtrusive and continuous monitoring of patients, especially at their place of residence, is becoming a significant part of the healthcare model. A variety of sensors are being used to monitor different patient conditions. Bed occupancy monitoring provides clinicians a quantitative measure of bed entry/exit patterns and may provide information relating to sleep quality. This paper presents a bed occupancy monitoring system using a bed pressure mat sensor. A clinical trial was performed involving 8 patients to collect bed occupancy data. The trial period for each patient ranged from 5-10 weeks. This data was analyzed using a participatory design methodology incorporating clinician feedback to obtain bed occupancy parameters. The parameters extracted include the number of bed exits per night, the bed exit weekly average (including minimum and maximum), the time of day of a particular exit, and the amount of uninterrupted bed occupancy per night. The design of a clinical user interface plays a significant role in the acceptance of such patient monitoring systems by clinicians. The clinician user interface proposed in this paper was designed to be intuitive, easy to navigate and not cause information overload. An iterative design methodology was used for the interface design. The interface design is extendible to incorporate data from multiple sensors. This allows the interface to be part of a comprehensive remote patient monitoring system.

Metrics to monitor performance of patients with mild cognitive impairment using computer based games

Mild Cognitive Impairment (MCI) results in a noticeable decrease in cognitive abilities but does not interfere with regular daily functions. Some patients with MCI may be able to return to age-appropriate cognitive abilities, but some will progress to dementia. Clinical interviews, tests and measurements are used to identify and monitor cognitive decline. Timely detection of cognitive decline provides an opportunity for early intervention and can improve care and quality of life. Periodic monitoring of the cognitive status of MCI patients in their own environment is a significant and cost effective aid in patient care. This paper presents a methodology and performance metrics for remote monitoring of cognitive ability using computer based Sudoku and word search games. We collected game data for 2 MCI patients from the Bruyére Memory Program over a period of weeks. Their game performance was then compared to results from cognitive testing using the Montreal Cognitive Assessment (MoCA) and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). The patient who performed better on the games also had higher scores on the cognitive testing.

Operating system performance measurements for Remote Patient Monitoring applications

The Remote Patient Monitoring (RPM) is becoming vital part of healthcare improving quality of care. The RPM system uses variety of sensors and wireless technologies to monitor multiple biological and environmental signals simultaneously providing status and trend data for the patient. The RPM system can also provide alarms/alerts for the patient or the caregiver in real-time so that the patient gets assistance in timely manner when an acute event occurs. The RPM system must detect such events in real-time to generate alarms/alerts. Use of mobile devices like smartphones and/or tablets for RPM enables patient mobility and provides real-time monitoring capability. The mobile device Operating System (OS) used for real-time RPM needs to meet the hard real-time requirements for alerts/alarms generation. The General Purpose OS (GPOS) uses fair scheduling algorithm for multitasking while Real Time OS (RTOS) uses preemptive scheduling. This paper evaluates the real-time performance of GPOS and a RTOS (QNX) under variety of load condition for RPM application. The results of the measurements indicate that the mobile device OS used for RPM must provide a prioritizing mechanism to satisfy the hard real-time requirements when the mobile device is multitasking and/or overloaded.

Differentiating assisted and unassisted bed exits using ultrasonic sensor

Monitoring bed exits is critical for establishing the mobility trend of a person. Sensors such as pressure sensitive mats have been used to monitor symmetry and timing of a sit to stand transfer to establish a mobility trend. In an uncontrolled setting, the timing and symmetry measurements for sit-to-stand transfers may be affected by friends, family and caregivers providing assistance during such transfer. It is of significant importance to differentiate assisted and unassisted transfers in order to accurately establish a mobility trend. This paper will use unobtrusive ultrasound sensors in order to monitor the presence of another person during the sit-to-stand transition. This paper will examine different sensor placements in order to optimize the detection area and minimize the undetected cases. A lab simulation was performed in a controlled setting comparing the different configurations. The optimal solution was verified in a hospital setting to maximize the detection of assisted vs. unassisted transfers. The results show an 86.2% coverage of the hospital room and an 80% successful detection rate of a third party. This allows for detection of assisted sit-to-stand transfer if the third party is present within this coverage area. We also demonstrate how passive infrared sensors (PIR) can be integrated in the proposed system to enhance room entry and exit detection.

Adaptive information content management and buffer caching design for robust real-time streaming over IP network

This paper presents robust adaptive information content system design using contiguous buffering scheme buffers for high data rate real-time applications like e-health, telemedicine and 3-D video using IP network. The design improves the resiliency of the realtime systems under adverse network conditions like congestion and/or temporary loss of connectivity and ensures that critical application data is not lost. The proposed adaptive information content management design for a high data rate real-time application shows how information content can be adaptively managed using contiguous sender buffer to reduce the data transfer rate when underlying network capacity changes over a time period, improving the survivability interval of the system. There is a tradeoff between loss of features, data rate reduction, criticality of the lost information and survivability time of the systems.