Alireza Vahdatpour

The SmartCane system: an assistive device for geriatrics

Falls are currently a leading cause of death from injury in the elderly. The usage of the conventional assistive cane devices is critical in reducing the risk of falls and is relied upon by over 4 million patients in the U.S.. While canes provide physical support as well as supplementary sensing feedback to patients, at the same time, these conventional aids also exhibit serious adverse effects that contribute to falls. The falls due to the improper usage of the canes are particularly acute in the elderly and disabled where reduced cognitive capacity accompanied by the burden of managing cane motion leads to increased risk. This paper describes the development of the SmartCane assistive system that encompasses broad engineering challenges that will impact general development of individualized, robust assistive and prosthetic devices. The SmartCane system combines advances in signal processing, embedded computing, and wireless networking technology to provide capabilities for remote monitoring, local signal processing, and real-time feedback on the cane usage. This system aims to reduce risks of injuries and falls by enabling training and guidance of patients in proper usage of assistive devices.

Accelerometer-based on-body sensor localization for health and medical monitoring applications

In this paper, we present a technique to recognize the position of sensors on the human body. Automatic on-body device localization ensures correctness and accuracy of measurements in health and medical monitoring systems. In addition, it provides opportunities to improve the performance and usability of ubiquitous devices. Our technique uses accelerometers to capture motion data to estimate the location of the device on the users body, using mixed supervised and unsupervised time series analysis methods. We have evaluated our technique with extensive experiments on 25 subjects. On average, our technique achieves 89% accuracy in estimating the location of devices on the body. In order to study the feasibility of classification of left limbs from right limbs (e.g., left arm vs. right arm), we performed analysis, based of which no meaningful classification was observed. Personalized ultraviolet monitoring and wireless transmission power control comprise two immediate applications of our on-body device localization approach. Such applications, along with their corresponding feasibility studies, are discussed.

Cluster size optimization in sensor networks with decentralized cluster-based protocols

Network lifetime and energy-efficiency are viewed as the dominating considerations in designing cluster-based communication protocols for wireless sensor networks. This paper analytically provides the optimal cluster size that minimizes the total energy expenditure in such networks, where all sensors communicate data through their elected cluster heads to the base station in a decentralized fashion. LEACH, LEACH-Coverage, and DBS comprise three cluster-based protocols investigated in this paper that do not require any centralized support from a certain node. The analytical outcomes are given in the form of closed-form expressions for various widely-used network configurations. Extensive simulations on different networks are used to confirm the expectations based on the analytical results. To obtain a thorough understanding of the results, cluster number variability problem is identified and inspected from the energy consumption point of view.

On-body device localization for health and medical monitoring applications

We present a technique to discover the position of sensors on the human body. Automatic on-body device localization ensures correctness and accuracy of measurements in health and medical monitoring systems. In addition, it provides opportunities to improve the performance and usability of ubiquitous devices. Our technique uses accelerometers to capture motion data to estimate the location of the device on the users body, using mixed supervised and unsupervised time series analysis methods. We have evaluated our technique with extensive experiments on 25 subjects. On average, our technique achieves 89% accuracy in estimating the location of devices on the body.

SmartFall: an automatic fall detection system based on subsequence matching for the SmartCane

Fall-induced injury has become a leading cause of death for the elderly. Many elderly people rely on canes as an assistive device to overcome problems such as balance disorder and leg weakness, which are believed to have led to many incidents of falling. In this paper, we present the design and the implementation of SmartFall, an automatic fall detection system for the SmartCane system we have developed previously. SmartFall employs subsequence matching, which differs fundamentally from most existing fall detection systems based on multi-stage thresholding. The SmartFall system achieves a near perfect fall detection rate for the four types of fall conducted in the experiments. After augmenting the algorithm with an assessment on the peak impact force, we have successfully reduced the false-positive rate of the system to close to zero for all six non-falling activities performed in the experiment.

Theoretical Bound and Practical Analysis of Connected Dominating Set in Ad Hoc and Sensor Networks

Connected dominating setis widely used in wireless ad-hoc and sensor networks as a routing and topology control backbone to improve the performance and increase the lifetime of the network. Most of the distributed algorithms for approximating connected dominating set are based on constructing maximal independent set. The performance of such algorithms highly depends on the relation between the size of the maximum independent set (mis(G)) and the size of the minimum connected dominating set (cds(G)) in the graph G. In this paper, after observing the properties of such subgraphs, we decrease the previous ratio of 3.453 to 3.0 by showing that mis(G) ≤ 3·mcds(G) + 3. Additionally, we prove that this bound is tight and cannot be improved. Finally, we present practical analysis of constructing connected dominating set based on maximal independent set in wireless networks. It is shown that the theoretical bound for unit disk graphis still practically applicable for general wireless networks.

Ubiquitous personal assistive system for neuropathy

The improvement in processor performance through continuous breakthroughs in transistor technology has resulted in the proliferation of lightweight embedded systems. Advances in wireless technology and embedded systems have enabled remote healthcare and telemedicine. Continuous and real-time monitoring can discretely analyze how a patients lifestyle affects his/her physiological conditions and if additional symptoms occur under various stimuli. Diabetes is one of most difficult challenges facing the health-care industry today. One of the primary afflictions of diabetic patients is peripheral neuropathy (loss of sensation in the foot). As a direct result of this condition, the likelihood of ulcer increases which in many cases leads to to amputation. We have developed a wireless electronic orthotics composed of lightweight embedded systems and non-invasive sensors which can be used by diabetic patients suffering from peripheral neuropathy. Our proposed system monitors feet motion and pressure distribution beneath the feet in real-time and classifies the state of the patient. The proposed system detects the conditions that could potentially cause a foot ulcer. This system enables a continuous feedback mechanism for instance in case of an undesired behavior or condition a preemptive message wirelessly to the patients cell phone/PDA/PC and over the WEB to the patients care-giver. This system can potentially reduce the amputation rates resulting from neuropathy by a huge factor.

Electronic orthotics shoe: Preventing ulceration in diabetic patients

The improvement in processor performance through continuous breakthroughs in transistor technology has resulted in the proliferation of lightweight embedded systems. Advances in wireless technology and embedded systems have enabled remote healthcare and telemedicine. Continuous and real-time monitoring can discretely analyze how a patients lifestyle affects his/her physiological conditions and if additional symptoms occur under various stimuli. Diabetes is one of most difficult challenges facing the healthcare industry today. One of the primary afflictions of diabetic patients is peripheral neuropathy (loss of sensation in the foot). As a direct result of this condition, the likelihood of ulcer increases which in many cases leads to to amputation. We have developed a wireless electronic orthotics composed of lightweight embedded systems and non-invasive sensors which can be used by diabetic patients suffering from peripheral neuropathy. Our proposed system monitors feet motion and pressure distribution beneath the feet in real-time and classifies the state of the patient. The proposed system detects the conditions that could potentially cause a foot ulcer. This system enables a continuous feedback mechanism for instance in case of an undesired behavior or condition a preemptive message wirelessly to the patient and the patients caregiver.

Leakage minimization using self sensing and thermal management

We have developed a system architecture, measuring and modeling techniques, and algorithms for on-line power and energy optimization and thermal management. The starting point for our approach is a simple and small gate-level network that can be used for real-time and low overhead measurement of temperature on chip positions where our network gates are placed. We use linear programming and interpolation to calculate the temperature at any arbitrary point of the integrated circuit. The periodic calculations of the temperature are used to estimate locally dissipated energies, which are consequently used to derive the most efficient use of operational times to minimize the overall leakage energy. All concepts and algorithms are experimentally validated using a simulation platform that consists of the Alpha 21364 processor and the SPEC benchmarks.

Energy minimization for real-time systems with non-convex and discrete operation modes

We present an optimal methodology for dynamic voltage scheduling problem in the presence of realistic assumption such as leakage-power and intra-task overheads. Our contribution is an optimal algorithm for energy minimization that concurrently assumes the presence of (1) non-convex energy-speed models as opposed to previously studied convex models, (2) discrete set of operational modes (voltages) and (3) intra-task energy and delay overhead. We tested our algorithm on MediaBench and task sets used in previous papers. Our simulation results show an average of 22% improvement in energy reduction in comparison with optimal algorithms for convex models without switching overhead and on average of 24% with consideration for energy and delay overheads. This analysis lays the groundwork for improving functionality in CAD design through non-convex techniques for discrete models.