Somatosensory Notification Alerts for Context-Aware User Interaction
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Solution Overview
Problem
Modern computing devices often fail to effectively alert users to notifications due to either missed attention or perceived distractions, as existing alert methods do not consider the user's physiological condition or activity at the time of notification.
Innovation Solution
A computing device that receives contextual information about the user's physiological condition and activity, selecting and outputting alerts such as electric stimulus, shape-memory alloy, or vibration alerts tailored to the user's state, ensuring the alert is perceived without causing distraction or annoyance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a notification alert is output to obtain user attention, then the user perceives the notification, but the alert causes distraction or annoyance
Solution Approach 1:
The alert characteristics are dynamically adjusted based on the user's current activity state and physiological condition. The system transitions from static alert delivery to dynamic adaptation, modifying alert intensity, type, and timing according to real-time contextual information about the user's state.
Solution Approach 2:
The system changes multiple parameters of the alert including intensity, duration, type (visual, audible, haptic), and timing based on contextual factors such as user activity level, physiological state, and environmental conditions. This allows the same notification to be delivered with different characteristics optimized for the current situation.
2Reliability
If alert intensity is increased to ensure perception, then user attention is obtained, but the alert becomes more disturbing
Solution Approach 1:
Different types of alerts (visual, audible, haptic) are applied to different sensory channels based on the user's current state. The system selects which sensory modality to use and adjusts the intensity locally for each type, rather than uniformly increasing all alert characteristics.
Solution Approach 2:
The system uses feedback from sensors that detect user physiological state and activity level to continuously adjust alert characteristics. This closed-loop approach allows the system to learn from user responses and optimize alert delivery to achieve perception with minimal disturbance.
3Reliability
If multiple alerts are output to ensure notification is noticed, then user attention is obtained, but power is consumed
Solution Approach 1:
The system performs preliminary assessment of the user's current state before delivering an alert, using sensor data and contextual information to predict the most effective alert type and intensity. This preliminary action avoids unnecessary alert iterations and reduces power consumption by getting the notification delivered correctly on the first attempt.
Solution Approach 2:
The system monitors its own alert effectiveness through user response detection and automatically adjusts future alert strategies without requiring manual intervention. This self-learning capability optimizes power usage by reducing redundant alerts while maintaining reliable notification delivery.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution increases the likelihood that users perceive notifications while minimizing disturbance, by adapting alert intensity based on contextual information, thus reducing the need for subsequent alerts and conserving power.
Implementation Method 1
a shape-memory alloy type alert
Data Source
AI summary
A computing device is described that can receive contextual information related to a user associated with the computing device. The contextual information may relate to at least one of a physiological condition of the user at a current time or a type of activity associated with the user at the current time. The computing device can select, based at least in part on the contextual information, a type of alert to output as an indication of notification data. The type of alert may include at least one of an electric stimulus type alert, a shape-memory alloy type alert, and a vibration type alert. Responsive to selecting the type of alert, the computing device can output an alert based on the notification data, the alert being of the selected type of alert.