This paper describes a method to evaluate daily physical activity by means of a portable device that determines the type of physical activity based on accelerometers and a barometer. Energy consumption of a given type of physical activity was calculated according to relative metabolic ratio (RMR) of each physical activity type that reflects exercise intensity of activities. Special attention was paid to classification algorithms for activity typing that identify detailed ambulatory movements considering vertical movements, such as stair/ slope climbing or use of elevators. A portable measurement device with accelerometers and a barometer, and a Kalman filter was designed to detect the features of vertical movements. Furthermore, walking speed was calculated by an equation which estimates the walking speed as a function of signal energy of vertical body acceleration during walking. To confirm the usefulness of the method, preliminary experiments were performed with healthy young and elderly subjects. The portable device was attached to the waist. A standard accelerometer based calorie counter was also attached for comparison. Experimental results showed that the proposed method feasibly classified the type of ambulatory physical activities; level walking, stair going up and down and elevator use. It was suggested that the consideration of vertical movements made a significant improvement in the estimation of energy consumptions, and the proposed method provides better estimation of physical activity compared to the conventional calorie counter.

Non-restricted estimate of three-dimensional (3D) walk trajectory during indoor locomotion is discussed. The walk trajectory is derived by the integration of the 3D acceleration of subject's foot. A sensor system is composed of an 3D accelerometer, three gyroscope, and one geomagnetic sensor and is attached on the tiptoe. Integral errors of the acceleration and the angular velocity are modified to keep the continuity of the velocity and the posture of the sensor system between the swing phase and the stance phase. Six subjects performed walk experiments including level walk, ascending, and descending in an office building to verify the proposed method. The experimental results show that the estimation error of 3D location to the actual walk distance is less than 10 [%] and the application of the proposed method improves the precise measurement of 3D walk trajectory.

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This paper describes a new method of walking speed estimation by a simple accelerometry of ambulatory movements, aimed at a precise quantification of energy consumption. It was postulated that walking speed variation reflects both strength and frequency of pelvis vibration during walking. Therefore, amplitudes of vertical acceleration that come along with walking speed variation were evaluated in terms of the signal energy in walking frequency band 1-3Hz. According to the Parseval's Theorem, signal energy can be applied both in time domain and frequency domain signal processing. The relationship between the walking speed and the signal energy was investigated considering aging. A portable instrument attaching on the waist measured vertical acceleration. Then, an estimate equation of walking speed as a function of signal energy was formulated from the experimental results of 199 subjects including young and elderly people. To validate the estimation, another 85 elderly people including 5 subjects who walked with the aid of sticks were investigated. The subjects were instructed to walk on a 16-meter strait level track at self-selected normal walking speed individually. Walking speed was estimated for 10 second continuous walking. Lap time was also measured to evaluate real walking speed. Results showed that the walking speed was accurately estimated by the proposed method (95%). It was also confirmed that this method could be applied to estimate the walking speed of both young and elderly people, but not those who walk with the aid of sticks.

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