Sleep Session Graph Time Axis Optimization
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Solution Overview
Problem
Existing sleep monitoring applications struggle to provide optimized visibility of sleep sessions across calendar periods, often breaking sleep sessions across days, which impairs user comprehension and resource efficiency.
Innovation Solution
A sleep application dynamically adjusts the time axis of sleep session graphs to ensure continuous representation of sleep sessions without breaks, optimizing visibility by iteratively determining the starting point that maximizes continuous sleep sessions, and centering data for enhanced user interaction and resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If sleep sessions are graphed using a fixed time axis range, then the graph structure is simple, but sleep sessions are broken across days which impairs user comprehension
Solution Approach 1:
The patent applies dynamics by making the time axis range adjustable rather than fixed. The system dynamically calculates and presents different time axis ranges based on the sleep data being displayed, allowing the graph to adapt to different viewing needs. This resolves the contradiction by enabling continuous sleep session representation (improving comprehension) while maintaining a relatively simple implementation through automated range calculation.
Solution Approach 2:
The patent changes the parameter of time axis range from a fixed value to a dynamically calculated range. By adjusting the time axis parameters based on the specific sleep data and viewing context, the system achieves continuous representation of sleep sessions without breaks, thereby improving user comprehension while the parameter adjustment is handled automatically in the background.
2Ease of operation
If the graph displays maximum continuous sleep sessions, then visibility is optimized, but the time axis range becomes more complex to determine
Solution Approach 1:
The system applies self-service by automatically calculating and optimizing the time axis range without requiring manual intervention. The graphing process autonomously determines the best time range to display maximum continuous sleep sessions, handling the complexity internally while presenting a simple, optimized result to the user. This resolves the contradiction by achieving visibility optimization through automated self-service processing.
Solution Approach 2:
The patent applies preliminary action by pre-calculating and determining the optimal time axis range before the actual graph rendering. The system performs the complex analysis of sleep data and time range optimization in advance, so that when the graph is displayed, the user immediately sees the optimized continuous representation without needing to understand or compute the underlying complexity.
3Productivity
If sleep data is transformed to center maximum data on the UI, then information density is improved, but data processing complexity increases
Solution Approach 1:
The patent applies parameter changes by transforming the sleep data parameters (timestamps, durations) to recalculate and reposition sleep sessions on the time axis. This data transformation centers the maximum amount of sleep data on the UI while maintaining continuous representation. The complexity is managed through automated parameter recalculation rather than manual processing.
Solution Approach 2:
The system replaces manual data processing with automated computational algorithms. Instead of requiring complex manual analysis to center data, the system uses computational methods to automatically transform and reposition sleep data parameters, achieving high information density through efficient algorithmic processing rather than mechanical complexity.
4Ease of operation
If the graph shows continuous sleep sessions without breaks, then user comprehension is improved, but more data needs to be rendered increasing resource consumption
Solution Approach 1:
The patent applies partial action by rendering only the necessary portion of sleep data that fits within the optimized time axis range. Rather than displaying all available data, the system calculates and renders only the continuous sleep sessions that can be properly represented without breaks, which reduces unnecessary data processing and resource consumption while maintaining comprehension.
Solution Approach 2:
The system uses parameter changes to dynamically adjust the data range and rendering parameters based on the optimized time axis calculation. By changing the data selection parameters to match the continuous representation goal, the system renders only the essential data needed for comprehension, avoiding unnecessary resource consumption from displaying redundant or broken data segments.
Data Source
AI summary
A sleep application running on a computing platform such as a server utilizes sleep data from a remote system that monitors a user's sleep behaviors and transforms the data to populate graphs of sleep sessions over various calendar periods (e.g., by week, by month) and render them on a user interface (UI) that is exposed to remote devices such as personal computers (PCs), tablets, multimedia consoles, and smartphones over a network. The sleep sessions are optimized for visibility on the remote devices by dynamically adjusting the range of the time axis of a graph so that a maximum number of sleep sessions over a calendar period may be graphed continuously over the range without breaks (which can impair visibility and reduce comprehension).