Invented by Bruce L. Davis, Edward B. Knudson, Geoffrey B. Rhoads, Tony F. Rodriguez, Colin P. Cornaby, Emma C. Sinclair, Eliot Rogers, Digimarc Corp

and apps for mental health therapy. In recent years, there has been a significant increase in the use of smartphone-based methods, systems, and apps for mental health therapy. With the widespread availability of smartphones and the growing recognition of the importance of mental health, these digital tools have become a popular and accessible option for individuals seeking therapy and support. One of the main reasons for the popularity of smartphone-based mental health therapy is the convenience it offers. Traditional therapy often requires scheduling appointments, commuting to a therapist’s office, and adhering to a set schedule. Smartphone-based therapy eliminates these barriers by allowing individuals to access therapy whenever and wherever they need it. This flexibility is particularly beneficial for those with busy schedules or limited access to mental health services. Another advantage of smartphone-based therapy is its cost-effectiveness. Traditional therapy can be expensive, with session fees and insurance coverage often being a barrier for many individuals. Smartphone-based therapy, on the other hand, is often more affordable, with some apps offering free or low-cost options. This makes therapy more accessible to a wider range of individuals, including those who may not have been able to afford traditional therapy. Furthermore, smartphone-based therapy provides a sense of anonymity and privacy. Some individuals may feel uncomfortable discussing their mental health issues face-to-face with a therapist. Smartphone-based therapy allows users to communicate through text, voice, or video, providing a level of anonymity that can make therapy more comfortable and accessible for those who may be hesitant to seek help otherwise. The market for smartphone-based methods, systems, and apps for mental health therapy is rapidly expanding. There are now a wide variety of apps available that cater to different mental health needs, such as anxiety, depression, stress management, and mindfulness. These apps often offer a range of features, including guided meditation, mood tracking, cognitive-behavioral therapy exercises, and access to licensed therapists through messaging or video calls. Many of these apps also incorporate artificial intelligence and machine learning algorithms to personalize the therapy experience. These algorithms analyze user data and provide tailored recommendations and interventions based on individual needs and preferences. This level of personalization can enhance the effectiveness of therapy and provide users with a more individualized and targeted approach to their mental health. However, it is important to note that smartphone-based therapy is not a replacement for traditional therapy. While these apps can be a valuable tool for self-help and support, they should not be used as a substitute for professional help, especially in cases of severe mental health conditions. It is always recommended to consult with a licensed therapist or healthcare professional for a comprehensive assessment and treatment plan. In conclusion, the market for smartphone-based methods, systems, and apps for mental health therapy is booming. These digital tools offer convenience, affordability, privacy, and personalization, making therapy more accessible to a wider range of individuals. However, it is crucial to remember that they should be used as a supplement to, rather than a replacement for, traditional therapy. With the right balance and guidance, smartphone-based therapy can be a valuable addition to the mental health support landscape.

The Digimarc Corp invention works as follows

Arrangements that involve portable devices (e.g. smartphones and tablets computers) have been disclosed. One arrangement allows content creators to choose the software that will render their content. This ensures continuity between artistic intent and delivery. Another uses a device camera for identifying nearby subjects and taking actions based on that information. Some others rely on near field chips (RFID), which allow for the identification of objects and audio streams (e.g. music, voice). Some technologies improve the user interfaces for such devices. Some arrangements allow discovery of both audio-visual content without the user having to switch between them. These devices can also be used for shopping, text entry and vision-based discoveries. Other improvements include architectural ones, such as those relating to evidence-based machines and blackboard systems. Other technologies include computational photography. There are many other features and arrangements that can be added to the photos.

Background for Smartphone-based methods, systems

The present technology expands in certain respects upon technology detailed in the above-detailed patent application. These previous works can be used to implement the present technology and can be incorporated into the current technology.

Referring to FIG. 1. An illustrative device 14 includes a processor 16, memory 18, one or several input peripherals 20 and one or two output peripherals 22. System 12 can also contain a network connection 24 and remote computers 26.

An illustrative device 14 can be a smartphone or tablet computer. However, any other electronic device that is consumer-grade can be used. The processor may include a microprocessor, such as an Atom device or A4 device. The operating system software and application software stored in the memory control part of the processor’s operation. ), data, etc. A hard drive or flash memory could be used as memory.

Input peripherals 20 could include a camera or a microphone. An interface system that converts analog signals from the camera/microphone into digital data is also possible. You can also use a touch screen or keyboard as an input peripheral. Output peripherals 22 include a speaker, display screen, and so on.

The 24th network connection can be wired (e.g. Ethernet, etc. ), wireless (WiFi, 4G, Bluetooth, etc. Or both.

In an exemplary operation device 14 receives a set digital content data through a microphone 20. The interface can be connected through the network connection 24 or any other means. You can use any content data; audio is an example.

The system 12 processes digital content data to create corresponding identification data. This can be done by using a digital watermark process or a fingerprinting algorithm. data (e.g., file names, header data, etc.). This data is used to identify the content data received from other data (e.g. other audio or video).

By referencing this identification data the system determines which software should be invoked. Indexing a table, database or other data structure with this identification data is one way to accomplish this. This will allow you to identify the correct software. FIG. 2 shows an illustration of a table. 2.

In certain cases, the data structure might identify a single program. If this is the case, the software will be launched. The software does not need to be installed on the device. Apps that are cloud-based may be available. If the software is not available, it can be downloaded from an online repository such as the iTunes Store, installed, and launched. The device can also subscribe to the software-as-service version of the app. Depending on the implementation, the user may be asked permission to participate in certain actions. In other cases, such actions are carried out without disturbing the user.

Sometimes, the data structure can identify multiple software programs. Different programs might be specific to certain platforms. In this case, device 12 could simply choose the program that corresponds to that platform (e.g. Android G2, iPhone 4, etc.). The data structure might identify other programs that are compatible with a particular platform. The device might check this situation to see if there are any already installed. It can launch the program if it is found. The device can choose between two programs if it finds them. The device might prompt the user to choose one or both. The device can choose to download an alternative program if none are available. This is done using an algorithm or user input. The application is launched once it has been downloaded and installed.

(Sometimes, the data structure might identify different programs that serve various functions?all of which are related to the content. One app could be used to find lyrics. An app that relates to the biography of a musician could be another. An app that allows you to purchase the content could be another option. Each type of software can include multiple alternatives.

Note: The device may have an already installed application that is technically suitable to work with the received content (e.g. to render an MPEG4 file or an MP3 file). There may be many or more programs that are technically compatible with certain operations. The content might indicate that only a small subset of the possible software programs should be used.

Software in the device 14 could enforce content-identified software selection. The system could also treat software identification as a preference that can be overridden by the user. In some cases, the user might be given an incentive to use content-identified software. Alternately, the user might be charged a fee or other impediment to use any software not identified by the content.

Sometimes, the system might not render certain content on a particular device (e.g. because there is no suitable app or hardware capability), but it may invite the user transfer the content to another device that has the required capability and may implement such transfer. Ansel Adams may have been sceptical of large format photographs being used as screen savers on a low resolution smartphone display. The software might suggest that the user instead of trying to display the images on a small format, low resolution smartphone display, it will ask the user to transfer the images to a larger format HD display at home.

The system might render the content in a limited manner, instead of rendering it completely. A video could be rendered in a series or still frames, such as from scene transitions. The system can also transfer the content to a place where it can be enjoyed more effectively. If hardware considerations allow (e.g. screen resolution is sufficient),?the software can be downloaded and installed.

As illustrated by the table in FIG. “As shown in FIG. 2 (which data structure might be located in the memory 18 or in a remote computing system 26, the indication of software could be based upon one or more contextual elements?in addition to content identification data.

Context” is a formal definition. “Context” is any information that can be used as a way to describe an entity’s situation (a person, place, or object that is relevant to the interaction between an application and a user), including applications themselves.

Computing context can include network connectivity, memory availability and CPU contention. User context (profile, location, actions and preferences, friends nearby, social networks, situation, etc.) Physical context (e.g. lighting, noise levels, traffic, heard sounds, recognized voices, etc. Temporal context (time, day, month and season), history of the above, etc. History of the above etc.

The taxonomy for contexts is a progression from simple to complex. It starts with location and then moves on to physical contexts (such as temperature, motion, 3D ambient sound, infrared and video), user or device actions, proximity (e.g. to people, buildings, boundaries, jurisdictions or other devices), somatics (e.g. live datastreams containing biometric data), data feeds (e.g. RSS feeds, notifications and updates from social networks, etc.), and

In the illustrated tableau, rows 32-34 correspond to the same content (i.e. the same content ID), but they indicate that different software should be used. Depending on whether the context is indoors and outdoors. The software is identified with a five symbol hex identifier, while the content is identified using six hex symbols. Other identifiers, with a longer or shorter length, may be used.

Row 36 shows two software items?both of these are invoked. One includes a second descriptor?an identifier for a YouTube video that will be loaded by software FF245. This software is intended for users in a daytime context and those aged between 20-25.

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