Abstract: An SMS-based human/computer interface that may be applied to a wide variety of tasks. The interface allows a human user to interact with a computer system using SMS messages. The user sends messages to the computer system and receives messages from the computer system in a format that would normally be used for interacting with a human acquaintance. The computer system includes a natural language processor with an associated lexicon of conventional language (such as English words) and SMS-unique language. The language processor determines the user's meaning and the system then generates responses that are appropriate within the present context The computer system includes the ability to bring in a human operator when conditions warrant such an intervention.

Abstract: An automated system for monitoring respiratory diseases, such as asthma, provides noninvasive, multimodal monitoring of respiratory signs and symptoms that can include wheeze and cough. Some embodiments employ a mobile device, such as a cell phone, in which raw data from a microphone and an accelerometer are processed, analyzed, and stored. Data can be collected continuously. Time domain and frequency domain analyses of signals to determine, e.g., energy, duration, and spectral content of candidate sounds can be employed to discriminate symptoms of interest from background sounds and to establish significance. Accelerometer signals are analyzed to determine activity levels. Analyses of a user's symptoms and activity level prior to, during, and after an event can provide meaningful determinations of disease severity and predict future respiratory events. The system can provide a summary of data, as well as an alarm when symptom severity reaches a threshold.

Abstract: An automated system for monitoring respiratory diseases, such as asthma, provides noninvasive, multimodal monitoring of respiratory signs and symptoms that can include wheeze and cough. Some embodiments employ a mobile device, such as a cell phone, in which raw data from a microphone and an accelerometer are processed, analyzed, and stored. Data can be collected continuously. Time domain and frequency domain analyses of signals to determine, e.g., energy, duration, and spectral content of candidate sounds can be employed to discriminate symptoms of interest from background sounds and to establish significance. Accelerometer signals are analyzed to determine activity levels. Analyses of a user's symptoms and activity level prior to, during, and after an event can provide meaningful determinations of disease severity and predict future respiratory events. The system can provide a summary of data, as well as an alarm when symptom severity reaches a threshold.