The IoT fall detection system detects the fall through the data classification of falling and daily living activity. It includes microcontroller board (Arduino Mega 2560), Inertial Measurement Unit sensor (Gy-521 mpu6050) and WI-FI module (ESP8266-01). There total ten (10) subjects in this project. The data of falling and non-falling (daily living activity) can be identified. The falling is the frontward fall, while the daily living activity includes standing, sitting, walking and crouching. K-nearest neighbour (k-NN) classifiers were used in the data classification. The accuracy of k-NN classifiers were 100% between falling and non-falling class. The feature was selected based on the percentage of accuracy of the k-NN classifier. The features of the Aareal.z (97.14%) and Angle.x (97.24%) were selected due to the good performance during the classification of the falling and non-falling class. The performance of the Aareal.z (58.41%) and Angle.x (57.78%) were satisfactory during the sub-classification of the non-falling class. Hence, the feature of Aareal.z and Angle.x were selected as the features which were implemented in the IoT fall detection device.

Generally, severity, any additional damage to the joint surface, and the optimal rehabilitation influence the recovery of an ankle injury. Optimal rehabilitation is the only approach for a human to heal as soon as possible. Ankle injury rehabilitation robots (AIRRs) are designed to fulfil the ideal rehabilitation by providing the required accuracy, consistency, and repeatability, compared to conventional rehabilitation methods. This review is to explore the performance of the existing AIRR using a SWOT analysis with a focus on the strengths and opportunities of an AIRR. Sources from journals and conference papers are selected for review after several screenings, according to the search conditions set by the authors. The results have shown a large group of AIRRs could accomplish all basic ankle motions and select parallel mechanisms to drive the foot platform. Most AIRRs provides crucial feedback sensors, such as position, torque, and angle. These factors determine the accuracy of the foot platform. Both the electrical/pneumatic actuation and wearable/platform-based AIRRs have their purpose for rehabilitation and must be considered as equal contributions to ankle injury rehabilitation research using robots. Opportunities to provide innovation to the already established AIRR research still exist in the ability to accommodate complex motion ankle rehabilitation exercises and to establish teaching and playback into the rehabilitation procedures for AIRRs. In general, the existing strengths of AIRRs provide advantages to patients where they can enhance the rehabilitation procedures while opportunities and knowledge gaps for AIRR research are still open to improvement.

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The simple needs of an ankle rehabilitation system are valid for medical evaluation, user-friendly, and perform efficiently at low cost. However, most of the current ankle rehabilitation systems face a lot of problems, such as inconvenient face-to-face therapy, manual evaluation by the physiotherapist, the limited number of physiotherapists, and the high cost. Therefore, the key conceptual issues in designing and implementing an ankle rehabilitation system are identified and discussed in this article in order to overcome these problems. The aim of designing an ankle rehabilitation system is to furnish an alternative for ankle sprain patients so that they can efficiently perform rehabilitation exercises in their household surroundings. Additionally, the output data from the ankle rehabilitation system provides valuable patient information for further medical evaluation and monitoring. This article describes the conceptual design phase of an ankle rehabilitation system. It starts with a needs analysis and focuses on conceptual design. Six concept options are designed based on the needs identified. The selected concept is decided based on the system needs and characteristics of the conventional ankle rehabilitation method. Finally, the preliminary implementation result is included to demonstrate the feasibility of the selected concept for the ankle rehabilitation system.

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