Patricia Kan

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This paper presents an automated system for a rehabilitation robotic device that guides stroke patients through an upper-limb reaching task. The system uses a partially observable Markov decision process (POMDP) as its primary engine for decision-making. The POMDP allows the system to automatically modify exercise parameters to account for the specific(More)
Stroke is the primary cause of adult disability. To support this large population in recovery, robotic technologies are being developed to assist in the delivery of rehabilitation. This paper presents an automated system for a rehabilitation robotic device that guides stroke patients through an upper-limb reaching task. The system uses a decision theoretic(More)
This paper presents a real-time system that guides stroke patients during upper extremity rehabilitation. The system automatically modifies exercise parameters to account for the specific needs and abilities of different individuals. We describe a partially observable Markov decision process (POMDP) model of a rehabilitation exercise that can capture this(More)
In this paper the approach of using a partially observable Markov model for games with dynamical difficulty adjustment is introduced. This approach leads implicitly to a strategy which balances gathering information about the player through his or her behavior with adjusting the game to the estimated player’s abilities and preferences. We will show how this(More)
PROBLEM The availability of less expensive and smaller ultrasound machines has enabled the use of ultrasound in virtually all major medical/surgical disciplines. Some medical schools have incorporated point-of-care ultrasound training into their undergraduate curriculum, whereas many postgraduate programs have made ultrasound training a standard. The(More)
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