Analysis of the Severity of Dyskinesia in Patients with Parkinsons Disease via Wearable Sensors

Patel, Shyamal; Sherrill, D.M.; Hughes, Richard L.; Hester, Todd; Huggins, N.; Lie-Nemeth, Theresa; Standaert, David G.; Bonato, Paolo

doi:10.1109/bsn.2006.10

Cited by 50 publications

(25 citation statements)

References 9 publications

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“…Hester et al [5] used accelerometers and linear regression models based on their measurements to predict functional ability scores for stroke rehabilitation. Patel et al [6] used clustering techniques to correlate accelerometer signals with the severity of dyskinesia in patients with Parkinson's disease. They demonstrated that patients with different severities can be represented by well separated clusters.…”

Section: Introductionmentioning

confidence: 99%

Beyond the standard clinical rating scales: Fine-grained assessment of post-stroke motor functionality using wearable inertial sensors

Zhang

Lange

Chang

et al. 2012

2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Accurate motor function assessment of post-stroke patients plays a critical role in their rehabilitation interventions. In this paper, we propose an approach to use wearable inertial sensing technology to quantitatively evaluate the patients' motor behavior. Different from existing wearable motor function assessment techniques that focus on building mapping functions that correlate sensed movement signals to the standard clinical rating scales, our approach provides a fine-grained assessment by capturing detailed patterns contained in the patients' movements. We collected data on three subjects including two post-stroke patients who have varying degrees of upper extremity hemiparesis. Our experimental results validate our approach and demonstrate that the captured patterns can be used to complement the standard clinical scores to provide fine-grained motor function assessment and help clinicians to track patients' gradual progress during rehabilitation.

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Section: Introductionmentioning

confidence: 99%

Beyond the standard clinical rating scales: Fine-grained assessment of post-stroke motor functionality using wearable inertial sensors

Zhang

Lange

Chang

et al. 2012

2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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“…Contemporary research in observation of human walking behavior using sensor networks has either focused on sensing motion using wearable monitoring devices [1] [2] or construction of mathematical models of walking patterns using techniques such as Switched Hidden Semi-Markov Models (S-HSMM) [3]. The former approach encumbers people with monitoring devices and requires them to carry it on their person at all times.…”

Section: Introductionmentioning

confidence: 99%

Observing Walking Behavior of Humans Using Distributed Phenomenon Detection and Tracking Mechanisms

Bose

Helal

2008

2008 International Symposium on Applications and the Internet

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The utility of walking parameters such as stride length, cadence and gait velocity for monitoring motor functions of patients suffering from brain injury, Parkinson's disease and obesity is well established. The application of sensor networks in this context has also been actively researched however; most of the research has focused either on construction of formal models of walking or design of wearable monitors. Unfortunately these approaches are not always practical for real-life monitoring, since they either require users to continuously wear monitoring equipment or rely on mathematical models which can be susceptible to significant prediction errors. In this paper we propose distributed mechanisms which utilize the concept of phenomenon detection and tracking for monitoring walking parameters. Our mechanisms do not require patients to be encumbered with monitoring devices and can track a subject's walk in real-time, in an energy efficient manner without a priori knowledge of a fixed mathematical model, thereby making it suitable for practical deployments.

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“…These applications and services include medical applications such as diagnostic techniques [9], health and stress monitoring [7], management of chronic diseases [5], and patient rehabilitation [1], as well as non medical applications and services such as biometrics [3], activity monitoring and learning [12] and sports and fitness tracking [4].…”

Section: Introductionmentioning

confidence: 99%

Energy efficient transmission strategies for Body Sensor Networks with energy harvesting

Seyedi

Sikdar

2008

2008 42nd Annual Conference on Information Sciences and Systems

103

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This paper addresses the problem of developing energy efficient transmission strategies for Body Sensor Networks (BSNs) with energy harvesting capabilities. It is assumed that two transmission modes that allow a tradeoff between the energy consumption and packet error probability are available to the sensors. Decision policies are developed to determine the transmission mode to use at a given instant of time in order to maximize the quality of coverage. The problem is formulated in a Markov Decision Process (MDP) framework and an upper bound on the performance of arbitrary policies is determined. Our results show that the quality of coverage associated with the MDP formulation outperforms the other policies.

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Analysis of the Severity of Dyskinesia in Patients with Parkinsons Disease via Wearable Sensors

Cited by 50 publications

References 9 publications

Beyond the standard clinical rating scales: Fine-grained assessment of post-stroke motor functionality using wearable inertial sensors

Beyond the standard clinical rating scales: Fine-grained assessment of post-stroke motor functionality using wearable inertial sensors

Observing Walking Behavior of Humans Using Distributed Phenomenon Detection and Tracking Mechanisms

Energy efficient transmission strategies for Body Sensor Networks with energy harvesting

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Analysis of the Severity of Dyskinesia in Patients with Parkinsons Disease via Wearable Sensors

Cited by 50 publications

References 9 publications

Beyond the standard clinical rating scales: Fine-grained assessment of post-stroke motor functionality using wearable inertial sensors

Beyond the standard clinical rating scales: Fine-grained assessment of post-stroke motor functionality using wearable inertial sensors

Observing Walking Behavior of Humans Using Distributed Phenomenon Detection and Tracking Mechanisms

Energy efficient transmission strategies for Body Sensor Networks with energy harvesting

Contact Info

Product

Resources

About

Analysis of the Severity of Dyskinesia in Patients with Parkinsons Disease via Wearable Sensors