BACKGROUND: Persons with Parkinson\'s disease (PwPD) suffer from motor and non-motor symptoms which significantly affect their quality of life (QoL), and the QoL of their care partners (CP). Tandem cycling reduces PwPD motor symptoms; however, no studies have examined other benefits or included PwPD CP. We conducted an 8-week community virtual reality (VR) tandem cycling intervention to assess the feasibility and efficacy for PwPD and their CP (i.e., PD dyads). We hypothesized that dyadic tandem cycling would improve (1) PwPD motor and non-motor symptoms and (2) dimensions of PD dyads\' QoL and physiologic health.
METHODS: Ten PD dyads were recruited to complete 8 weeks of progressive intensity, bi-weekly tandem cycling. At pre- and post-testing, PwPD were assessed using the Movement Disorder Society-Unified Parkinson\'s Disease Rating Scale-III (MDS-UPDRS-III), functional gait assessment (FGA), and 10-m gait speed test. PD dyads also completed emotional and cognitive status questionnaires [e.g., Geriatric Depression Scale-Short Form (GDS-SF)], and wore BodyGuard 2 heart rate (HR) monitors for 48 h to assess surrogate measures of heart rate variability. Statistical analyses were conducted using Student\'s t tests with significance set at p ≤ 0.05.
RESULTS: Eight PD dyads and one PwPD completed the intervention. Retention of PwPD (90%) and CP (80%) was adequate, and PD dyad adherence ranged from 91.67 to 97.91%. PwPD demonstrated significant clinical improvements in MDS-UPDRS-III scores (- 7.38, p < 0.01), FGA scores (+ 3.50, p < 0.01), and 10-m gait speed times (+ 0.27 m/s, p < 0.01), in addition to significant self-reported improvements in mobility (- 13.61, p = 0.02), fatigue (- 5.99, p = 0.02), and social participation (+ 4.69, p < 0.01). CP depressive symptoms significantly decreased (- 0.88, p = 0.02), and PD dyads shared a significant increase in root mean square of the successive differences (RMSSD; p = 0.04).
CONCLUSIONS: Our pilot study demonstrated feasibility and multiple areas of efficacy supporting further investigation of community VR tandem cycling as a therapeutic intervention for PD dyads.

Increased awareness, recognition, and accessibility has led to an increase in the popularity of adaptive cycling. This article aims to provide up-to-date information for clinicians about available adaptations, participation options, and resources. We review the para-cycling classification system and 4 main categories of cycles. There are multiple considerations for fit and customization depending on an individual\'s disability to improve efficiency and comfort. Virtual platforms that allow riders to train and compete online have grown in popularity among para-cycling communities and offer an alternative to riding outdoors. Many national and local organizations offer communities and grants to assist with adaptive equipment.

Recent studies in rehabilitation of Parkinson\'s disease (PD) have shown that cycling on a tandem bike at a high pedaling rate can reduce the symptoms of the disease. In this research, a smart motorized bicycle has been designed and built for assisting Parkinson\'s patients with exercise to improve motor function. The exercise bike can accurately control the rider\'s experience at an accelerated pedaling rate while capturing real-time test data. Here, the design and development of the electronics and hardware as well as the software and control algorithms are presented. Two control algorithms have been developed for the bike; one that implements an inertia load (static mode) and one that implements a speed reference (dynamic mode). In static mode the bike operates as a regular exercise bike with programmable resistance (load) that captures and records the required signals such as heart rate, cadence and power. In dynamic mode the bike operates at a user-selected speed (cadence) with programmable variability in speed that has been shown to be essential to achieving the desired motor performance benefits for PD patients. In addition, the flexible and extensible design of the bike permits readily changing the control algorithm and incorporating additional I/O as needed to provide a wide range of riding experiences. Furthermore, the network-enabled controller provides remote access to bike data during a riding session.