Ramin Fallahzadeh

• PhD
• PostDoc Position at Stanford University

Background Medication nonadherence is a critical problem with severe implications in indi-viduals at risk for atherosclerotic cardiovascular disease. Many studies have attempted to predict medication adherence in this population, but few, if any, have been effective in prediction, sug-gesting that essential risk factors remain unidentified. Object...

Fluid intake tracking is crucial in providing interventions that assist individuals to stay hydrated by maintaining an adequate amount of fluid. It also helps to manage calorie intake by accounting for the amount of calorie consumed from beverages. While staying hydrated and controlling calorie intake is critical in both physical wellness and cogni...

Recent years have witnessed growing research on autonomous activity recognition models for use in new settings. However, it lacks comprehensive frameworks for transfer learning, specifically, the ability to deal with partially available data in new settings. To address these, we propose OptiMapper, a novel uninformed cross-subject transfer learning...

Wearable step counters, also referred to as activity trackers, have been developed for health and activity monitoring, as well as for step tracking. These trackers, however, produce unreliable measurements during slow walking and when walking with assistive devices (i.e., aided walking). To address this challenge, in this article, we introduce, Pa...

Power consumption is identified as one of the main complications in designing practical wearable systems, mainly due to their stringent resource limitations. When designing wearable technologies, several system-level design choices, which directly contribute to the energy consumption of these systems, must be considered. In this article, we propose...

Activity recognition, as an important component of behavioral monitoring and intervention, has attracted enormous attention, especially in Mobile Cloud Computing (MCC) and Remote Health Monitoring (RHM) paradigms. While recently resource constrained wearable devices have been gaining popularity, their battery life is limited and constrained by the...

In this review, we describe state-of-the-art digital health solutions for geriatric oncology and explore the potential application of emerging remote health-monitoring technologies in the context of cancer care. We also discuss the benefits and motivations behind adopting technology for symptom monitoring of older adults with cancer. We provide an...

Purpose of review: The purpose of this review is to explore state-of-the-art remote monitoring and emerging new sensing technologies for in-home physical assessment and their application/potential in cancer care. In addition, we discuss the main functional and non-functional requirements and research challenges of employing such technologies in re...

Smartphone prompts and notifications are popular because they provide users with timely and important information. However, they can also be an annoyance if they pop up at inopportune times and interrupt important tasks. In this paper we introduce Thyme, an intelligent notification front end that uses activity recognition and machine learning to id...

Developing machine learning algorithms for applications of Internet-of-Things requires collecting a large amount of labeled training data, which is an expensive and labor-intensive process. Upon a minor change in the context, for example utilization by a new user, the model will need retraining to maintain the initial performance. To address this p...

Background As commercially available activity trackers are being utilized in clinical trials, the research community remains uncertain about reliability of the trackers, particularly in studies that involve walking aids and low-intensity activities. While these trackers have been tested for reliability during walking and running activities, there h...

Activity recognition systems are widely used in monitoring physical and physiological conditions as well as observing the short/long term behavioral patterns for the purpose of improving the health and well-being of the users. The major obstacle in widespread use of these systems is the need for collecting labeled data to train the activity recogni...

One of major challenges in chronic disease self-management is the lack of medication adherence. Despite the proliferation of mobile technologies, the potential of using pervasive computing solutions for improved medication management has remained almost unexplored. In this paper, we present a smart-phone based system capable of delivering adaptive...

We present a novel approach for monitoring beverage intake. Our system is composed of an ultrasonic sensor, an RGB color sensor, and machine learning algorithms. The system not only measures beverage volume but also detects beverage types. The sensor unit is lightweight that can be mounted on the lid of any drinking bottle. Our experimental results...

With the proliferation of wearable devices in the Internet-of-Things applications, designing highly power-efficient solutions for continuous operation of these technologies in life-critical settings emerges. We propose a novel ultra-low power framework for adaptive compressed sensing in activity recognition. The proposed design uses a coarse-graine...

Wearable monitoring devices for ubiquitous health care are becoming a reality that has to deal with the battery autonomy of the devices. Several research areas are focusing their efforts to reduce the energetic impact in these motes: from efficient micro-architectures, to on-node data processing techniques. In this paper we focus in the optimizatio...

Background: It is unclear whether subgroups of patients may benefit from remote monitoring systems (RMS) and what user characteristics and contextual factors determine effective use of RMS in patients with heart failure (HF). Objective: The study was conducted to determine whether certain user characteristics (i.e. personal and clinical variable...

Designing remote health monitoring systems requires a multi-faceted perspective that takes into account requirements and contexts imposed by the medical application, technology and end-user. We study such a design perspective in the context of remote and real-time edema monitoring. Edema (accumulation of fluid in certain soft-tissues) is regarded a...

Many studies have reported that glaucoma patients experience mobility issues, such as walking slowly and bumping into obstacles frequently. However, little is known to date about how a person's gait is impacted due to glaucoma. This paper presents design and development of a gait analysis approach using a shoe-integrated sensing system and accompan...

The utility of wearables is currently limited to lab experiments and controlled environments mainly because computational algorithms embedded in wearables fail to produce accurate measurements in uncontrolled, dynamically changing, and potentially harsh environments. With the exponentially growing adoption of these systems in human-centered Interne...

Wearable motion sensors are widely used to estimate metabolic equivalent of task (MET) values associated with physical activities. However, one major obstacle in widespread adoption of current wearables is that any changes in configuration of the network requires new data collection and re-training of the underlying signal processing algorithms. Fo...

Ankle edema is one the most significant symptoms for monitoring patients with chronic systematic diseases. It is an important indicator of onset or exacerbation of a variety of diseases that disturb cardiovascular, renal, or hepatic system such as heart, liver, and kidney failure, diabetes, etc. The current approaches toward edema assessment is con...

Intervention strategies can help individuals with cognitive impairment to increase adherence to instructions, independence, and activity engagement and reduce errors on everyday instrumental activities of daily living (IADLs) and caregiver burden. However, to be effective, intervention prompts should be given at a time that does not interrupt other...

Wearables are being widely utilized in health and wellness applications, primarily due to the recent advances in sensor and wireless communication, which enhance the promise of wearable systems in providing continuous and real-Time monitoring and interventions. Wearables are generally composed of hardware/software components for collection, process...

Biometric gait analysis using wearable sensors offers an objective and quantitative method for gait parameter extraction. However, current techniques are constrained to specific platform parameters, and hence significantly lack generality, scalability and sustainability. In this paper, we propose a platform-independent and self-adaptive approach fo...

Leg swelling produced by retention of fluid in leg tissues is known as peripheral edema, which is regarded as a symptom for various systematic diseases such as heart or kidney failure. In current clinical practice, edema is manually assessed by clinical experts. Such an assessment can often be inaccurate and unreliable especially if it is made by d...

In this paper, we present a novel routing algorithm in order to avoid deadlock and packet dropping. In our proposed algorithm the network-on-chip (NoC) is capable of tolerating faults in presence of control faults in combinational parts of routers. In addition, by modifying the functionality of the router, the router is enabled to test its own, as...