Abstract: A decorative assembly for covering and decorating a light fixture on a ceiling, the decorative assembly comprising a decoration with an upper end and a lower end opposite the upper end, the decoration comprises a frame adjacent the upper end and has an open central portion that is unobstructed. A ceiling magnet is configured to be directly attached to the ceiling for the decorative assembly. A frame magnet extends from the frame inward toward the open central portion for detachably coupling with the ceiling magnet and is configured to secure the decoration to the ceiling. The decorative assembly does not comprise the light fixture and, when assembled, no part of the decorative assembly contacts the light fixture.

Abstract: A motion-activated mechanical sound-emitting device includes at least one ringer and at least one striker supported outside the ringer. A user actuator selects between an on state, in which motion permits the striker to contact the ringer to emit sound, and an off state, in which contact is prevented by moving one or both components away from one another or by interposing a blocker. Striker-support components remain outside the ringer, with no portion disposed within or passing through the ringer. The device is operable in any orientation and, in some embodiments, is spring-free and provides intermediate positions for partial sound reduction. The device can be mounted to a wide variety of moving hosts, such as a bicycle, backpack strap, pet collar, horn of a saddle, wheelchair, motorized scooter, or robot, and may employ multiple striker-ringer pairings.

Abstract: A sound emitting device can include electrically powered components that emit sound. In addition, the device can have a sensor capable of detecting movement of the device, and an electrically powered circuit. When the sensor is activated, the circuit can send a signal to the device to cause the device to emit sound. An attachment device can couple the device to a person, animal, bicycle, other device or a combination thereof.

Abstract: A method is disclosed for using an artificial intelligence engine to present a user interface capable of presenting the progress of a user in domains. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive measurements as input, and outputting, based on the measurements, a user interface that causes icons to dynamically change position on the user interface. While a user performs an exercise using the exercise device, the method includes receiving the measurements from sensors associated with the exercise device. The method includes presenting, on a computing device associated with the exercise device, sections of the user interface, wherein the sections are each related to a separate domain comprising the domains and wherein, based on the measurements, each section includes the icons placed.

Abstract: A method is disclosed for using an artificial intelligence engine to interact with a user of an exercise device during an exercise session. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive data as input, and based on the data, providing an output. While a user performs an exercise using the exercise device, the method includes receiving the data from an input peripheral of a computing device associated with the user. Based on the data being received from the input peripheral, the method includes determining, via the machine learning model, the output to control an aspect of the exercise device.

Abstract: A decorative assembly for covering and decorating a light fixture on a ceiling, the decorative assembly comprising a decoration with an upper end and a lower end opposite the upper end, the decoration comprises a frame adjacent the upper end and has an open central portion that is unobstructed. A ceiling magnet is configured to be directly attached to the ceiling for the decorative assembly. A frame magnet extends from the frame inward toward the open central portion for detachably coupling with the ceiling magnet and is configured to secure the decoration to the ceiling. The decorative assembly does not comprise the light fixture and, when assembled, no part of the decorative assembly contacts the light fixture.

Abstract: A method is disclosed for using an artificial intelligence engine to present a user interface capable of presenting the progress of a user in domains. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive measurements as input, and outputting, based on the measurements, a user interface that causes icons to dynamically change position on the user interface. While a user performs an exercise using the exercise device, the method includes receiving the measurements from sensors associated with the exercise device. The method includes presenting, on a computing device associated with the exercise device, sections of the user interface, wherein the sections are each related to a separate domain comprising the domains and wherein, based on the measurements, each section includes the icons placed.

Abstract: A method is disclosed for using an artificial intelligence engine to interact with a user of an exercise device during an exercise session. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive data as input, and based on the data, providing an output. While a user performs an exercise using the exercise device, the method includes receiving the data from an input peripheral of a computing device associated with the user. Based on the data being received from the input peripheral, the method includes determining, via the machine learning model, the output to control an aspect of the exercise device.

Abstract: A method is disclosed for using an artificial intelligence engine to perform a control action. The control action is based on one or more measurements from a wearable device. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive the one or more measurements as input, and outputting, based on the one or more measurements, a control instruction that causes the control action to be performed. The method includes receiving the one or more measurements from the wearable device being worn by a user, determining whether the one or more measurements indicate, during an interval training session, that one or more characteristics of the user are within a desired target zone, and responsive to determining that the one or more measurements indicate the one or more characteristics of the user are not within the desired target zone during the interval training session, performing the control action.

Abstract: A method is disclosed for using an artificial intelligence engine to modify resistance of one or more pedals of an exercise device. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive one or more measurements as input, and outputting, based on the one or more measurements, a control instruction that causes the exercise device to modify the resistance of the one or more pedals. The method includes receiving the one or more measurements from a sensor associated with the one or more pedals of the exercise device, determining whether the one or more measurements satisfy a trigger condition, and responsive to determining that the one or more measurements satisfy the trigger condition, transmitting the control instruction to the exercise device.

Abstract: A method is disclosed for using an artificial intelligence engine to perform a control action. The control action is based on measurements from a wearable device. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive the measurements as input, and outputting, based on the measurements, a control instruction that causes the control action to be performed. The method includes receiving the measurements from the wearable device being worn by a user, determining whether the measurements indicate, during an interval training session, that one or more characteristics of the user are within a desired target zone, and responsive to determining that the measurements indicate the one or more characteristics of the user are not within the desired target zone during the interval training session, performing the control action.

Abstract: A method is disclosed for using an artificial intelligence engine to present a user interface capable of presenting the progress of a user in domains. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive measurements as input, and outputting, based on the measurements, a user interface that causes icons to dynamically change position on the user interface. While a user performs an exercise using the exercise device, the method includes receiving the measurements from sensors associated with the exercise device. The method includes presenting, on a computing device associated with the exercise device, sections of the user interface, wherein the sections are each related to a separate domain comprising the domains and wherein, based on the measurements, each section includes the icons placed.

Abstract: A method is disclosed for using an artificial intelligence engine to modify resistance of pedals of an exercise device. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive measurements as input, and outputting, based on the measurements, a control instruction that causes the exercise device to modify, independently from each other, the resistance of the pedals. While a user performs an exercise using the exercise device, the method includes receiving the measurements from sensors associated with the pedals. The method includes determining, based on the measurements, a quantifiable or qualitative modification to the resistance provided by a pedal of the pedals. The resistance provided by another pedal of the pedals is not modified. The method includes transmitting the control instruction to the exercise device to cause the resistance provided by the pedal to be modified.

Abstract: A method is disclosed for using an artificial intelligence engine to modify resistance of one or more pedals of an exercise device. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive one or more measurements as input, and outputting, based on the one or more measurements, a control instruction that causes the exercise device to modify the resistance of the one or more pedals. The method includes receiving the one or more measurements from a sensor associated with the one or more pedals of the exercise device, determining whether the one or more measurements satisfy a trigger condition, and responsive to determining that the one or more measurements satisfy the trigger condition, transmitting the control instruction to the exercise device.

Abstract: A rehabilitation and exercise system can include a base. A static device can be coupled to the base and configured to provide isometric exercise for a user by receiving static force from the user to facilitate at least one of osteogenesis or muscle hypertrophy for the user. In addition, a dynamic device can be coupled to the base and configured to provide a dynamic exercise for the user by being moved by the user to facilitate at least one of osteogenesis and muscle hypertrophy for the user.

Abstract: A method is disclosed for using an artificial intelligence engine to modify resistance of pedals of an exercise device. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive measurements as input, and outputting, based on the measurements, a control instruction that causes the exercise device to modify, independently from each other, the resistance of the pedals. While a user performs an exercise using the exercise device, the method includes receiving the measurements from sensors associated with the pedals. The method includes determining, based on the measurements, a quantifiable or qualitative modification to the resistance provided by a pedal of the pedals. The resistance provided by another pedal of the pedals is not modified. The method includes transmitting the control instruction to the exercise device to cause the resistance provided by the pedal to be modified.

Abstract: A method is disclosed for using an artificial intelligence engine to interact with a user of an exercise device during an exercise session. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive data as input, and based on the data, providing an output. While a user performs an exercise using the exercise device, the method includes receiving the data from an input peripheral of a computing device associated with the user. Based on the data being received from the input peripheral, the method includes determining, via the machine learning model, the output to control an aspect of the exercise device.

Abstract: A method is disclosed for using an artificial intelligence engine to present a user interface capable of presenting the progress of a user in domains. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive measurements as input, and outputting, based on the measurements, a user interface that causes icons to dynamically change position on the user interface. While a user performs an exercise using the exercise device, the method includes receiving the measurements from sensors associated with the exercise device. The method includes presenting, on a computing device associated with the exercise device, sections of the user interface, wherein the sections are each related to a separate domain comprising the domains and wherein, based on the measurements, each section includes the icons placed.

Abstract: A support structure has a base with a top and recesses. Inserts are mounted in respective ones of the recesses. Each insert has a protrusion that extends from the insert. The inserts are reversible and invertible. The inserts include: a first configuration where the protrusions extend above the top of the base and are located in a first position; a second configuration where the protrusions extend above the top of the base and are located in a second position that differs from the first position; and a third configuration where the protrusions extend into the recesses below the top of the base such that the inserts are flush with the top of the base.

Abstract: A method is disclosed for using an artificial intelligence engine to interact with a user of an exercise device during an exercise session. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive data as input, and based on the data, providing an output. While a user performs an exercise using the exercise device, the method includes receiving the data from an input peripheral of a computing device associated with the user. Based on the data being received from the input peripheral, the method includes determining, via the machine learning model, the output to control an aspect of the exercise device.