A portable sit-stand elliptical exercise machine includes a seat, a transmission wheel installed at the seat, two linkage mechanisms installed at the transmission wheel, and two mobile pedals respectively installed at the linkage mechanisms. Each linkage mechanism includes a driving portion connected to the transmission wheel, an axle portion disposed at one side away from the transmission wheel, and an adjustment portion disposed between the axle portion and the driving portion. Each mobile pedal is pivotally connected to the axle portion and includes a plurality of assembly portions. Thus, an angle is formed between each mobile pedal assembled to one of the assembly portions and the linkage mechanism to facilitate a user to utilize the portable sit-stand elliptical exercise machine in either a sitting or standing posture, thereby solving issue of a conventional solution that cannot be applied for a dual use of both sitting and standing postures.

A mounting frame for releasably securing a pedal exerciser to a table is disclosed. The mounting frame includes a frame assembly having a pair of generally opposed end members dimensioned to extend across an upper surface of the table and configured to receive feet of the pedal exerciser, and a pair of generally opposed side members connected to the pair of generally opposed end members at corresponding ends thereof, so as to cooperatively define a central aperture therewith with the pair of generally opposed side members configured to engage opposite sides of the table. The frame assembly further includes a first strap dimensioned to extend across the central aperture and engage the pair of generally opposed side members so as to releasably secure the table therebetween.

Motion resistance apparatuses and methods of use and, more specifically, leg-actuated motion resistance apparatuses configured for positioning beneath a fixed surface and for engagement by a seated user.

A stepper exercise machine is provided. When a pedal is pedaled by a user, a drive gear is rotated forward or rearward. One end of a link is rotated about a drive rod, and a turning lever connected to the other end of the link is confined by a second accommodation trough of the pedal, so that the link brings the pedal to move in the up-down direction and the front-rear direction. In cooperation with a shaft which is fixed, a sleeve is rotatable relative to the shaft. When the pedal is driven, a first accommodation space provides a space for the pedal to move in the front-rear direction. By means of the action of two flywheels to provide an acceleration effect, the rotation of the drive gear is to speed up, so that the user can reduce the force exerted to the pedal.

A method includes receiving a set of treatment plans. Each treatment plan comprising the set of treatment plans may be associated with a user capable of using a treatment device to perform the associated treatment plan. The method also includes receiving healthcare professional profile information. The method also includes identifying treatment device information for each treatment device capable of being used by a cohort of users associated with respective treatment plans. The method also includes using an artificial intelligence engine, wherein the artificial intelligence engine uses at least one machine learning model configured to generate resource deployment predictions, to generate at least one resource deployment prediction. The at least one machine learning model may generate the at least one resource deployment prediction based on at least some treatment plans comprising the set of treatment plans, at least some of the healthcare professional profile information, and at least some of the treatment device information.

Systems and methods for identifying a condition of a user. A treatment apparatus is configured to be manipulated by the user for performing an exercise, and an interface is communicably coupled to the treatment apparatus. One or more sensors are configured to sense one or more characteristics of an anatomical structure of the user. A processing device and a memory is communicatively coupled to the processing device. The memory includes computer readable instructions, that when executed by the processing device, cause the processing device to: receive, from the sensors, one or more sensor inputs representative of the one or more of characteristics of the anatomical structures; calculate an infection probability of a disease based on the one or more characteristics of the anatomical structures; and output, to the interface, a representation of the infection probability.

A computer-implemented system may include a treatment device configured to be manipulated by a user while the user is performing a treatment plan, a patient interface comprising an output device configured to present telemedicine information associated with a telemedicine session, and a first computing device configured to: receive treatment data pertaining to the user while the user uses the treatment device to perform the treatment plan; identify at least one aspect of the at least one measurement pertaining to the user associated with a first treatment device mode of the treatment device; determine whether the at least one aspect of the measurement correlates with a secondary condition of the user; and, in response to a determination that the at least one aspect of the at least one measurement is correlated with the at least one secondary condition of the user, generate secondary condition information indicating at least the secondary condition.

An exercise apparatus includes a pedal main part on which a user U in a sitting posture places his/her foot, a pedal support part configured to support the pedal main part so that the pedal main part is movable within a predetermined range along a foot-length direction, and a guiding mechanism configured to guide the pedal support part so that the pedal support part moves along a predetermined rotational trajectory in a cyclic manner. According to the above-described configuration, it is possible to prevent each of joints such as a hip joint, a knee joint, and an ankle joint from moving outside the range of movement of the joint. The exercise apparatus may also include a rubber tube that resists the movement of the pedal main part relative to the pedal support part.

Systems, methods, and computer-readable mediums for generating, by an artificial intelligence engine, one or more alignment plans for aligning a user with an imaging sensor. The method comprises generating one or more machine learning models trained to identify alignment plans. The method also comprises receiving user data and determining that a targeted portion of a body of the user is outside of a field of view of the imaging sensor. The method further comprises generating the one or more alignment plans using the one or more machine learning models. Each of the one or more alignment plans comprises a target location within the field of view of the imaging sensor and one or more elements for adjusting the targeted portion of the body from a first location to the target location. The method also comprises transmitting the one or more alignment plans to a computing device.

A computer-implemented system for processing medical claims is disclosed. The system includes a medical device configured to be manipulated by a user while the user performs a treatment plan; a patient interface associated with the medical device, the patient interface comprising an output configured to present telemedicine information associated with a telemedicine session; and a processor. During the telemedicine session, the processor is configured to receive information from a medical device. Using the device-generated information, the processor is further configured to determine device-based medical coding information. The processor is further configured to transmit the device-based medical coding information to a claim adjudication server.