Techniques for classifying sleep sessions
US-2016192218-A1 · Jun 30, 2016 · US
US2016239609A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2016239609-A1 |
| Application number | US-201514624534-A |
| Country | US |
| Kind code | A1 |
| Filing date | Feb 17, 2015 |
| Priority date | Feb 17, 2015 |
| Publication date | Aug 18, 2016 |
| Grant date | — |
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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).
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What is claimed: 1 . A server device configured for controlling access to data from a remote client device over a network, comprising: one or more processors; a storage component arranged to receive read and write commands from the one or more processors; a network interface for supporting communications with the remote client device; and one or more memories storing computer-readable instructions which, when executed by the one or more processors, perform a method for controlling access to data from the remote client device comprising the steps of iteratively applying a graphing process to determine a number of sleep sessions that are expressible continuously on a sleep graph having the a time axis and a calendar axis based on different beginning times for a range on a time axis, storing results from the graphing process for each of the different beginning times in the storage component, selecting a beginning time for the range from the stored results that provides a maximum number of continuously expressible sleep sessions, and controlling access by the remote client device to the sleep graph. 2 . The server device of claim 1 further including generating the sleep graph using the selected beginning time, the sleep graph expressing sleep sessions over a calendar period. 3 . The server device of claim 2 further including exposing user controls to the remote device to enable one of selecting the calendar period or controlling one or more aspects of the generating. 4 . The server device of claim 2 in which the generating is performed to centrally locate the sleep sessions in the sleep graph. 5 . The server device of claim 2 in which the calendar period includes one of days, weeks, or months. 6 . The server device of claim 1 further including configuring the sleep graph to include distributed sleep sessions and wrap one or more sleep sessions over boundaries in the calendar period. 7 . The server device of claim 1 further including obtaining sleep data from a second remote client device, the second remote client device being configured as a companion to a wearable device having sensors to gather the sleep data. 8 . The server device of claim 7 further including transforming the sleep data from the second remote client device to generate the sleep sessions. 9 . The server device of claim 8 further including obtaining sleep session start and end times from the sleep data. 10 . The server device of claim 1 further including exposing the sleep graph to a browser running on the remote client device. 11 . One or more computer-readable memories storing instructions which, when executed by one or more processors disposed in a computer server, control data received by a remote client device over a network, comprising: obtaining sleep data over a calendar period that describes sleep behaviors of a user from data obtained from one or more sensors; determining starting times and ending times for sleep sessions occurring over the calendar period from the sleep data; initiating a graphing process for a sleep graph having a time axis and calendar axis by selecting an initial beginning time for a range of times expressed on the time axis; calculating a number of sleep sessions for which visibility is optimized on the sleep graph using a time range spanning the beginning time and a maximum end time for the sleep sessions; storing a result of the calculating in a storage component available to the server; incrementing the beginning time by an interval and repeating the calculating and storing until the calculating has been performed over a predetermined time period; adjusting the time axis to use a range having a beginning time that provides a maximum number of visibility optimized sleep sessions over the calendar period; and transmitting the sleep graph with the adjusted time axis to the remote client over the network. 12 . The one or more computer-readable memories of claim 11 in which visibility is optimized using sleep sessions that are continuously expressed without breaks and the predetermined time period is 24 hours. 13 . The one or more computer-readable memories of claim 11 further including determining sleep quality using the sleep data. 14 . The one or more computer-readable memories of claim 13 further including configuring the sleep graph to express the sleep quality. 15 . The one or more computer-readable memories of claim 14 in which the sleep quality includes one of light sleep, restful sleep, or wakefulness. 16 . The one or more computer-readable memories of claim 11 further including adjusting the calendar axis on the sleep graph to capture one or more additional sleep sessions. 17 . A method for optimizing visibility of sleep sessions over a calendar period on a device, the method comprising the steps of: communicating with a wearable device that is configured for collecting biometric data from a wearable device user, transforming the collected biometric data into sleep data describing sleep behaviors of the user; and rendering a sleep graph on user interface of the device, the rendered sleep graph being configured to optimize visibility of sleep sessions derived, at least in part, from the sleep data, the optimization including rendering a majority of the sleep sessions in a continuous, non-broken manner in the sleep graph. 18 . The method of claim 17 in which the optimization is implemented using an automated graphing process and further includes substantially locating a majority of the sleep sessions in a central portion of the sleep graph. 19 . The method of claim 17 further including transmitting the sleep data to a remote service over a network. 20 . The method of claim 18 further including one of generating the sleep graph locally on the device or receiving the sleep graph from the remote service over the network.
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