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Form attractiveness is an important catalyst driving consumer preference for a particular product. However, a designer faces two major difficulties when attempting to enhance the attractiveness of a product form. First, consumer perception regarding form attractiveness involves a number of different intricate psychological and circumstantial evaluation bases. Second, variability exists between different consumer's perceptions of the same product form. This study treats the task of satisfying consumer needs/desires for product form as a multi-objective design activity and develops a product form optimization method, which combines the Taguchi method with the TOPSIS algorithm. A case study involving the design of a passenger car form targeted at a particular consumer group is presented to demonstrate the operational procedure involved in the proposed method and to verify its performance. The results of the verification experiments confirm that the optimized design has a higher attractiveness in terms of each evaluation basis and results in a more consistent consumer evaluation than the non-optimized designs. The method proposed in this study is straightforward to implement and provide an effective means of reducing the time and costs associated with product form design.

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Consumers' psychological perceptions of a product are significantly influenced by its appearance aesthetics, and thus product form plays an essential role in determining the commercial success of a product. The evolution of a product's form during the design process is typically governed by the designer's individual preferences and creative instincts. As a consequence, there is a risk that the product form may fail to satisfy the consumers' expectations or may induce an unanticipated consumer response. This study commences developing an integrated design approach based on the numerical definition of product form. A series of evaluation trials are then performed to establish the correlation between the product form features and the consumers' perceptions of the product image. The results of the evaluation trials are used to construct three different types of mathematical model (a multiple regression analysis model, a backpropagation neural network model, and a multiple regression analysis with a backpropagation neural network model) to predict the likely consumer response to any arbitrary product form. The feasibility of an integrated design approach is demonstrated using a three-dimensional knife form. Although this study takes an example for illustration and verification purposes, the methodology proposed in the present study is equally applicable to any form of consumer product.

For more than a decade, many countries have been actively developing robotic assistive devices to assist in the rehabilitation of individuals with limb disability to regain function in the extremities. The exoskeleton assistive device in this study has been designed primarily for hemiplegic stroke patients to aid in the extension of fingers to open up the palm to simulate the effects of rehabilitation. This exoskeleton was designed as an anterior-support type to achieve palmar extension and acts as a robotic assistive device for rehabilitation in bilateral upper limb task training. Testing results show that this wearable exoskeleton assistive device with human factor consideration using percentile dimensions can provide comfortable wear on patients as well as adequate torque to pull individual fingers into flexion towards the palm for rehabilitation. We hope this exoskeleton device can help stroke patients with loss of function in the upper extremities to resume motor activities in order to maintain activities of daily living.

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