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Maximizing healthy life expectancy is essential for enhancing well-being. Optimal exercise intensity is crucial in promoting health and ensuring safe rehabilitation. Since heart rate is related to exercise intensity, the required exercise intensity is achieved by controlling the heart rate. This study aims to control heart rate during exercise by dynamically adjusting the load on a bicycle ergometer using a proportional-integral (PI) control. The choice of PI parameters is very important because the PI parameters significantly affect the performance of heart rate control. Since the dynamic characteristics of heart rate relative to work rate vary widely from subject to subject, the PI parameters for each subject must be determined individually. In this study, PI parameters are optimized directly from exercise data using a data-driven design approach. Thus, the proposed method does not require excessive exercise of the subject to model heart rate dynamics. Using the proposed method, the heart rate can be controlled to follow a designed reference model so that the heart rate is safely increased to the desired value. The quantitative evaluation of the control results of fifteen healthy volunteers confirmed that the proposed method improved the control error of the target heart rate trajectory by approximately 40%, regardless of gender or age. In addition, it was shown that control parameters from the exercise experiment also indicate that females are more likely than males to have an elevated heart rate at the same load., (© 2024. The Author(s).)

We propose a new home health care network for the acquisition and transmission of data from ordinary home health care appliances based on IEEE11073. In this study, we develop a standard protocol for data collection and a simple interface to accommodate different monitoring systems that make use of different data protocols. The system provides for one-way data transmission, thus saving power and conforming to Japanese pharmaceutical law. Our standardized protocol was verified during a 1-year field test involving 20 households in Japan. Data transmission errors between home health care devices and the home gateway were 4.21 per a day with our newly developed standard protocol. Over a 1 year period, we collected and analyzed data from 241,000 separate sources associated with healthy, home-based patients and chronically ill, clinic-based patients, the latter through physician intervention. We evaluate some of the possible applications for collecting daily health care data and introduce some of our findings relating primarily to body weight and blood pressure monitoring for elderly subjects in their own homes.

Intralimb incoordination needs to be distinguished from interlimb incoordination, which is observed in Parkinson's disease (PD). With this aim, intra and inter-limb coordination impairment in the lower limbs were measured in 13 patients with cerebellar ataxia during pedaling of an ergometer with left and right pedals that can be rotated independently. Intralimb incoordination in patients with cerebellar ataxia was compared with interlimb incoordiation in patients with PD. We concluded that impairment of intralimb coordination in ataxia patients leads to inability to maintain pedaling amplitude and speed, but unlike in PD, right and left coordination was roughly preserved. Our method may be useful for assessing the severity of ataxia and detecting hidden parkinsonism in ataxic patients.

To classify lower limb dynamics in patients with Parkinson's disease (PD), we conducted a clinical study by using pedaling exercise.Twenty-seven patients with idiopathic PD were included in this study. We measured rotational velocities of pedals during pedaling movements with a newly developed ergometer. The velocity waveforms exhibited different characteristics among patients, which could be categorized into four different clusters. In cluster 1, the amplitude on each side was constant and the relative phase was locked at 180 degrees. The pattern was the same as seen in normal subjects. In cluster 2, the amplitude on each side was constant, but the relative phase was locked at 90 degrees. In cluster 3, the amplitude on each side was modulated, and the relative phase drifted monotonously from 0 to 360 degrees during pedaling cycles. In cluster 4, the amplitude on each side was synchronously and irregularly modulated, and the relative phase fluctuated with intermittent spike-like decrement. In order to evaluate, the correlation between pattern and severity of PD, we divided 13 patients, who underwent measurement of pedaling patterns more than three times, into three groups, and found that the abnormal coordination pattern correlated with the presence of freezing phenomenon in patients with PD. Our clinical analysis may contribute in analyzing and classifying the dynamics of PD.

Coordination between the left and right limbs during cyclic movements, which can be characterized by the amplitude of each limb's oscillatory movement and relative phase, is impaired in patients with Parkinson's disease (PD). A pedaling exercise on an ergometer in a recent clinical study revealed several types of coordination disorder in PD patients. These include an irregular and burst-like amplitude modulation with intermittent changes in its relative phase, a typical sign of chaotic behavior in nonlinear dynamical systems. This clinical observation leads us to hypothesize that emergence of the rhythmic motor behaviors might be concerned with nonlinearity of an underlying dynamical system. In order to gain insight into this hypothesis, we consider a simple hard-wired central pattern generator model consisting of two identical oscillators connected by reciprocal inhibition. In the model, each oscillator acts as a neural half-center controlling movement of a single limb, either left or right, and receives a control input modeling a flow of descending signals from higher motor centers. When these two control inputs are tonic-constant and identical, the model has left-right symmetry and basically exhibits ordered coordination with an alternating periodic oscillation. We show that, depending on the intensities of these two control inputs and on the difference between them that introduces asymmetry into the model, the model can reproduce several behaviors observed in the clinical study. Bifurcation analysis of the model clarifies two possible mechanisms for the generation of disordered coordination in the model: one is the spontaneous symmetry-breaking bifurcation in the model with the left-right symmetry. The other is related to the degree of asymmetry reflecting the difference between the two control inputs. Finally, clinical implications by the model's dynamics are briefly discussed.