The goal of this clinical trial is to explore how walking combined with different levels of partial blood flow restriction (BFR) affects cardiovascular, neuromuscular, and movement (kinematic) variables in older adults.
The main questions it aims to answer are:
Does walking with BFR increase internal effort, as shown by cardiovascular changes, and is this effect proportional to the level of restriction?
Does walking with BFR temporarily reduce neuromuscular control, and is this reduction greater at higher restriction levels?
Does walking with BFR change gait movement patterns?
This study uses a crossover design, meaning that each participant will complete all four conditions and serve as their own control.
Participants will:
Take part in walking sessions under four conditions with different levels of restriction: BFR40%, BFR80%, SHAM (0% BFR), and CON (without BFR).
Have their cardiovascular responses, muscle performance, and gait movement patterns measured.
Report their perceptions of the sessions, including Rate of Perceived Exertion (RPE), satisfaction, and possible side effects.
None
Being institutionalized.
Peripheral vascular disease, defined by an ankle-brachial index (ABI) outside the normal range (0.9-1.4).
Uncontrolled arterial hypertension (>180/110 mmHg).
Any contraindication to exercise, based on self-reported medical history and PAR-Q+.
Crossover
Walking
BehavioralParticipants will perform two continuous 10-minute walking bouts, separated by a 3-minute seated recovery period to allow reperfusion following BFR or pause, along a rectangular 40-meter walking circuit (15×5 m). Walking cadence will be standardized at 112 steps per minute.
Blood pressure
Systolic, diastolic and mean blood pressure will be obtained by a photoplethysmography sensor. Units: mmHg
Heart rate
The average and maximum values will be obtained using a chest-worn heart rate sensor. Unit: beats per minute (bpm)
RR-Interval Time-Domain Metrics
Standard time-domain HRV metrics-including mean RR intervals (meanRR), the standard deviation of normal-to-normal intervals (SDNN), and the root mean square of successive differences (RMSSD)-will be derived from inter-beat interval data exported from a chest-worn heart rate sensor (epochs of 5 min). Units: milliseconds (ms).
RR-Interval Nonlinear Metric
Short-term fractal scaling (DFA α1) will be calculated from inter-beat interval data exported from a chest-worn heart rate sensor (epochs of 5 min). Units: dimensionless.
Arterial stiffness
It will be assessed by finger-toe pulse wave velocity (PWV) method. Units: m/s
Temporal Gait Parameters
Mean temporal gait parameters-including stride time, step time, and stance time-will be derived from IMU-based measurements. Units: milliseconds (ms).
Temporal Gait Variability
Stride-to-stride temporal variability (stride time, step time, stance time) will be computed from walking recordings collected using a wearable inertial measurement unit (IMU) equipped with a triaxial accelerometer and gyroscope. Variability will be expressed as the coefficient of variation (CV) for each temporal metric. Units: Percentage (%)
Postural Stability
Postural stability in mediolateral (ML) and anterior-posterior (AP) directions will be assessed during quiet standing under four conditions (eyes open/closed × firm/foam surface). A wearable IMU will record triaxial centre-of-mass acceleration. Stability metrics will be computed as -ln\[m/s²\], where higher values reflect lower acceleration and therefore better postural control. Units: -ln\[m/s²\]
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Universidade da Coruña
Lead sponsor
Ministry of Work and Welfare - Xunta de Galicia
Collaborator
Universidade do Porto
Collaborator
University of La Laguna
Collaborator
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